Papers + Code - MIT-IBM Watson AI Lab

Ensemble Estimation of Information Divergence

Information Theory

Gradient Descent for Spiking Neural Networks

Deep Learning

Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Causal Inference

Action Centered Contextual Bandits

Deep Learning

BlockDrop: Dynamic Inference Paths in Residual Networks

Computer Vision

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning.

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning

Robustness Natural Language Processing

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Efficient AI Deep Learning

Learning to Separate Object Sounds by Watching Unlabeled Video

Computer Vision

The Sound of Pixels

Multimodal Learning Computer Vision

Learning to Teach in Cooperative Multiagent Reinforcement Learning

Multi-agent Systems Reinforcement Learning

Dialog-based Interactive Image Retrieval

NeurIPS Computer Vision

Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

CVPR Computer Vision

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization

Optimization Deep Learning

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks

Robustness Optimization

Delta-encoder: an effective sample synthesis method for few-shot object recognition

Computer Vision Few-shot Learning

Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification

CVPR

Sparse, Smart Contours to Represent and Edit Images

CVPR

Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning

CVPR

Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions

ICML

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

Robustness Explainability

Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation

Generative Models

Deriving Machine Attention from Human Rationales

EMNLP Natural Language Processing

emrQA: A Large Corpus for Question Answering on Electronic Medical Records

AI in Healthcare Natural Language Processing

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

Generative Models Graph Deep Learning

Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency

ECCV

Interpretable Basis Decomposition for Visual Explanation

ECCV

Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input

ECCV Multimodal Learning

Learning Entropic Wasserstein Embeddings

Machine Learning Optimal Transport

signSGD via Zeroth-Order Oracle

Optimization Robustness

Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding

Neuro-Symbolic AI Computer Vision

MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

AI in Healthcare Deep Learning

Experimental Design for Cost-Aware Learning of Causal Graphs

Causal Inference

StNet: Local and Global Spatial-Temporal Modeling for Action Recognition

Computer Vision Time Series

Co-regularized Alignment for Unsupervised Domain Adaptation

Transfer Learning Deep Learning

Unsupervised learning with contrastive latent variable models

Unsupervised Learning

Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems

Multi-agent Systems

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Generative Models Explainability

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks

Robustness

Scalable Graph Learning for Anti-Money Laundering: A First Look

AI in Finance Graph Deep Learning

Efficient Neural Network Robustness Certification with General Activation Functions

NeurIPS

HOGWILD!-Gibbs Can Be PanAccurate

NeurIPS

How Does Batch Normalization Help Optimization?

NeurIPS

Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction

NeurIPS

Direct Estimation of Differences in Causal Graphs

NeurIPS

The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

NeurIPS

Learning and Testing Causal Models with Interventions

NeurIPS

Neural Network Robustness Certification with General Activation Functions

Robustness Deep Learning

Weakly Supervised Dense Event Captioning in Videos

Computer Vision

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

Robustness

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach

ICML

A Sequential Set Generation Method for Predicting Set-Valued Outputs

AAAI

MAi : An Intelligent Model Acquisition Interface for Interactive Specification of Dialogue Agents

AAAI

Tight Certificates of Adversarial Robustness

Cybersecurity NeurIPS

Moments in Time Dataset: one million videos for event understanding

Computer Vision Multimodal Learning

Structural Supervision Improves Learning of Non-Local Grammatical Dependencies

Natural Language Processing

Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

Computer Vision

Unsupervised learning by competing hidden units

PNAS Unsupervised Learning

Towards Optimal Transport with Global Invariances

AISTATS Optimal Transport

Support and Invertibility in Domain-Invariant Representations

AISTATS

Size of Interventional Markov Equivalence Classes in Random DAG Models

AISTATS

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery

AISTATS

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Neuro-Symbolic AI Computer Vision

Learning Embeddings into Entropic Wasserstein Spaces

ICLR

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

ICLR

Bayesian Nonparametric Federated Learning of Neural Networks

Federated Learning

Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

Graph Deep Learning Natural Language Processing

Variational Russian Roulette for Deep Bayesian Nonparametrics

Deep Learning Bayesian Modeling

Write, Execute, Assess: Program Synthesis with a REPL

Program Synthesis

Molecular Hypergraph Grammar with Its Application to Molecular Optimization

ICML

Estimating Information Flow in Deep Neural Networks

ICML

AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

ICML

Scalable Fair Clustering

ICML

Collective Model Fusion for Multiple Black-Box Experts

ICML

Dirichlet Simplex Nest and Geometric Inference

ICML

Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications

ICML

Grounding Spoken Words in Unlabeled Video

CVPR

Additive Adversarial Learning for Unbiased Authentication

CVPR

Unsupervised learning of action classes with continuous temporal embedding

CVPR

HAQ: Hardware-Aware Automated Quantization With Mixed Precision

CVPR

Identifying Interpretable Action Concepts in Deep Networks

CVPR

Deep Leakage from Gradients

Robustness Deep Learning

Unsupervised Grounding of Plannable First-Order Logic Representation from Images

ICAPS

Towards Stable Symbol Grounding with Zero-Suppressed State AutoEncoder

ICAPS

Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering

Computer Vision Time Series

Attributed Description Logics: Reasoning on Knowledge Graphs

IJCAI

Neural language models as psycholinguistic subjects: Representations of syntactic state

Natural Language Processing Time Series

Unsupervised Clinical Language Translation

KDD

Adversarially Robust Submodular Maximization under Knapsack Constraints

KDD

Retaining Privileged Information for Multi-Task Learning

KDD

Coupled Variational Recurrent Collaborative Filtering

KDD

Local Unsupervised Learning for Image Analysis

Unsupervised Learning Computer Vision

Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations

IJCAI

Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively

IJCAI

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective

IJCAI

DDL: Deep Dictionary Learning for Predictive Phenotyping

IJCAI

RDPD: Rich Data Helps Poor Data via Imitation

IJCAI

The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence

Computational neuroscience Computer Vision

Defensive Quantization: When Efficiency Meets Robustness

Efficient AI Robustness

Watch, Reason and Code: Learning to Represent Videos Using Program

Computer Vision

Seeing What a GAN Cannot Generate

Generative Models

Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference

Lifelong Learning Transfer Learning

The Future of Work: How New Technologies Are Transforming Tasks

Future of Work

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

ICCV

Reasoning about Human-Object Interactions through Dual Attention Networks

ICCV Computer Vision

Cross-channel Communication Networks

NeurIPS Deep Learning

Out-of-Domain Detection for Low-Resource Text Classification Tasks

EMNLP

Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

EMNLP

Context-Aware Conversation Thread Detection in Multi-Party Chat

EMNLP

Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets

ACL Natural Language Processing

TWEETQA: A Social Media Focused Question Answering Dataset

ACL

Self-Supervised Learning for Contextualized Extractive Summarization

ACL

Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers

ACL

Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

ACL

SimVAE: Simulator-Assisted Training for Interpretable Generative Models

Generative Models Explainability

Reverse-engineering causal graphs with soft interventions

Causal Inference

New tricks from old dogs: multi-source transfer learning

Transfer Learning Explainability

Class-wise rationalization: teaching AI to weigh pros and cons

Natural Language Processing Deep Rationalization

Causal inference is expensive. Here’s an algorithm for fixing that.

Causal Inference

Visual Concept-Metaconcept Learning

Neuro-Symbolic AI

Alleviating label switching with optimal transport

Optimal Transport

Topics are more meaningful than words. AI for comparative literature.

Natural Language Processing Optimal Transport

Imitation learning from observations

Deep Learning

Using geometry to understand documents

Natural Language Processing

SPAHM: Parameter matching for model fusion

Bayesian Modeling

Big-Little-Video-Net: Work smarter, not harder, for video understanding

Computer Vision

ZO-AdaMM: Derivative-free optimization for black-box problems

Optimization NeurIPS

Scalable inference of topic evolution via models for latent geometric structures

NeurIPS

Sample Efficient Active Learning of Causal Trees

NeurIPS

Adversarial Examples Are Not Bugs, They Are Features

NeurIPS

ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

NeurIPS

Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement

NeurIPS

Statistical Model Aggregation via Parameter Matching

NeurIPS

Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers

NeurIPS

Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions

NeurIPS

Hierarchical Optimal Transport for Document Representation

NeurIPS

A Game Theoretic Approach to Class-wise Selective Rationalization

NeurIPS

Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks

NeurIPS

Image Synthesis with a Single (Robust) Classifier

NeurIPS

Private Testing of Distributions via Sample Permutations

NeurIPS

Sobolev Independence Criterion

NeurIPS

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

NeurIPS

Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference

Deep Learning Bayesian Modeling

Point-Voxel CNN for Efficient 3D Deep Learning

NeurIPS Efficient AI

Embedding Compression with Isotropic Iterative Quantization

Natural Language Processing

Automating machine learning with a joint selection framework

AAAI AutoML

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph Deep Learning AAAI

A content-aware attack generator for AI cybersecurity

Adversarial Machine Learning Cybersecurity

MULE: Multimodal Universal Language Embedding

AAAI

Robust Low-Rank Discovery of Data-Driven Partial Differential Equations

AAAI

Top-Quality Planning: Finding Practically Useful Sets of Best Plans

AAAI

Towards Certificated Model Robustness Against Weight Perturbations

AAAI

CASTER: Predicting drug interactions with chemical substructure representation

AAAI

CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator

AAAI

Fastened crown: Tightened neural network robustness certificates

AAAI

A unifying framework for expectation-aware AI planning

Automated Planning

Reading between the lines with graph deep learning for NLP

Natural Language Processing AAAI

Online AI planning with graph neural networks and adaptive scheduling

Automated Planning Graph Deep Learning

On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Optimization

Sentence Embedding Alignment for Lifelong Relation Extraction

Natural Language Processing Lifelong Learning

Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

AI in Finance Graph Deep Learning

Self-supervised Moving Vehicle Tracking with Stereo Sound

Multimodal Learning Computer Vision

The sound of motions

Computer Vision

TSM: Temporal Shift Module for Efficient Video Understanding

Efficient AI Computer Vision

Graph Convolutional Networks for Temporal Action Localization

Graph Deep Learning Computer Vision

On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

Optimization Robustness

LaSO: Label-Set Operations networks for multi-label few-shot learning

Computer Vision Few-shot Learning

SpotTune: Transfer Learning through Adaptive Fine-tuning

Computer Vision Transfer Learning

RepMet: Representative-based metric learning for classification and one-shot object detection

Computer Vision

ObjectNet: A bias-controlled dataset object recognition

Computer Vision NeurIPS

CASTER: An AI framework for preventing adverse reactions to medication

AI in Healthcare AAAI

Adversarial Robustness vs Model Compression, or Both?

Robustness

Reshaping Diverse Planning

Automated Planning

Location-aware Graph Convolutional Networks for Video Question Answering

AAAI

Deep Symbolic Superoptimization Without Human Knowledge

Neuro-Symbolic AI Optimization

A Closer Look at Deep Policy Gradients

Optimization ICLR

Deep Audio Priors Emerge From Harmonic Convolutional Networks

Audio Processing Deep Learning

Once for All: Train One Network and Specialize it for Efficient Deployment

Efficient AI ICLR

Implementation Matters in Deep RL: A Case Study on PPO and TRPO

Reinforcement Learning Optimization

Generative Ratio Matching Networks

Generative Models Deep Learning

Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence

Entrepreneurship Future of Work

Learning Rate Rewinding for elegant neural network pruning

Efficient AI Deep Learning

Layer-wise federated learning with FedMA

Federated Learning

Learning to learn with distributional signatures for text data

ICLR Transfer Learning

Fast and efficient black-box testing for AI cybersecurity

Cybersecurity Robustness

CLEVRER: The first video dataset for neuro-symbolic reasoning

Neuro-Symbolic AI Computer Vision

Why Gradient Clipping accelerates training for neural networks

Optimization Efficient AI

SenSR: the first practical algorithm for individual fairness

AI Fairness Robustness

Sign-OPT: Defending the hard-label black-box cyber attack

Cybersecurity Adversarial Machine Learning

Federated Adversarial Domain Adaptation

ICLR

Why Gradient Clipping Accelerates Training: A Theoretical Justification For Adaptivity

ICLR

Sign Bits Are All You Need For Black-box Attacks

ICLR

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

CVPR

Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning

CVPR

Towards Verifying Robustness of Neural Networks against Semantic Perturbations

CVPR

Dense Regression Network for Video Grounding

CVPR

Relationship Matters: Relation Guided Knowledge Transfer for Incremental Learning of Object Detectors

CVPR Computer Vision

Bio-Inspired Hashing for Unsupervised Similarity Search

ICML Neuroscience

Proper Network Interpretability Helps Adversarial Robustness in Classification

ICML

Unsupervised Speech Decomposition via Triple Information Bottleneck

ICML

Invariant Rationalization

ICML

Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks

ICML

Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion

ICML

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition

ECCV Computer Vision

Characterization of Overlap in Observational Studies

AISTATS Machine Learning

COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder

ECCV

Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency

AISTATS Optimal Transport

Auditing ML Models for Individual Bias and Unfairness

AISTATS Machine Learning

We Have So Much in Common: Modeling Semantic Relational Set Abstractions in Videos

ECCV Computer Vision

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

ECCV Computer Vision

TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification

ECCV Computer Vision

OnlineAugment: Online Data Augmentation with Less Domain Knowledge

ECCV Computer Vision

A Broader Study of Cross-Domain Few-Shot Learning

ECCV Computer Vision

DataMix: Efficient Privacy-Preserving Edge-Cloud Inference

ECCV

Foley Music: Learning to Generate Music from Videos

ECCV Computer Vision

Adversarial T-shirt! Evading Person Detectors in A Physical World

ECCV Computer Vision

Learning to Scale Multilingual Representations for Vision-Language Tasks

ECCV

Does enforcing fairness mitigate biases caused by subpopulation shift?

NeurIPS

Universal Domain Adaptation through Self Supervision

Transfer Learning Unsupervised Learning

MCUNet: Tiny Deep Learning on IoT Devices

Deep Learning Efficient AI

Approximate Cross-Validation for Structured Models

NeurIPS

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning

Computer Vision Multimodal Learning

Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation

NeurIPS

Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes

NeurIPS

The Lottery Ticket Hypothesis for the Pre-trained BERT Networks

Efficient AI

Continuous Regularized Wasserstein Barycenters

Optimal Transport

Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning

Efficient AI

Auxiliary Task Reweighting for Minimum-data Learning

NeurIPS

Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment

NeurIPS

Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations

NeurIPS Neuroscience

Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance

Bayesian Modeling

Training Stronger Baselines for Learning to Optimize

Optimization

Applications of Common Entropy in Causal Inference

Causal Inference

Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning

Causal Inference

Entropic Causal Inference: Identifiability and Finite Sample Results

Causal Inference

Higher-Order Certification For Randomized Smoothing

Optimization

Debiased Contrastive Learning

NeurIPS

Learning Restricted Boltzmann Machines With Sparse Latent Variables

NeurIPS

Differentiable Augmentation for Data-Efficient GAN Training

Optimization

Robust Federated Learning: The Case of Affine Distribution Shifts

Federated Learning

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth

NeurIPS

Online Bayesian Goal Inference for Boundedly-Rational Planning Agents

NeurIPS

Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models

NeurIPS

Active Structure Learning of Causal DAGs via Directed Clique Trees

Causal Inference

CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models

NeurIPS

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

NeurIPS

Testing Determinantal Point Processes

NeurIPS

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

NeurIPS

Learning Physical Graph Representations from Visual Scenes

NeurIPS

Black Loans Matter: Fighting Bias for AI Fairness in Lending

AI Fairness AI in Finance

Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations

NeurIPS

Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS)

IJCAI

The Computational Limits of Deep Learning

Efficient AI Deep Learning

Do Neural Networks Really Need to Be So Big?

Efficient AI Deep Learning

Can a Fruit Fly Learn Word Embeddings?

ICLR Computation and Language

Large Associative Memory Problem in Neurobiology and Machine Learning

ICLR

On Learning Continuous Pairwise Markov Random Fields

AISTATS

Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization

AISTATS

Directed Acyclic Graph Neural Networks

ICLR Graph Deep Learning

Discrete Graph Structure Learning for Forecasting Multiple Time Series

ICLR Time Series

VA-RED^2: Video Adaptive Redundancy Reduction

ICLR Computer Vision

AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition

ICLR Computer Vision

Improved Mutual Information Estimation

AAAI

Fast Training of Provably Robust Neural Networks by SingleProp

AAAI

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning

ICML Machine Learning

Dense Associative Memory for Pattern Recognition

NeurIPS Neural and Evolutionary Computing

Adversarial Option-Aware Hierarchical Imitation Learning

ICML Machine Learning

Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study

TACL Computation and Language

Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations

NAACL Computation and Language

Multilingual BERT Post-Pretraining Alignment

NAACL Computation and Language

Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning

EMNLP Computation and Language

Outlier-Robust Optimal Transport

ICML

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?

ICML

Auto-NBA: Efficient and Effective Search Over The Joint Space of Networks, Bitwidths, and Accelerators

ICML

Global Prosody Style Transfer Without Text Transcriptions

ICML

AGENT: A Benchmark for Core Psychological Reasoning

ICML Artificial Intelligence

Complementary Evidence Identification in Open-Domain Question Answering

EACL Computation and Language

Learning-based Support Estimation In Sublinear Time

ICLR

Anycost GANs for Interactive Image Synthesis and Editing

CVPR Computer Vision

Black-box Explanation of Object Detectors via Saliency Maps

CVPR Computer Vision

Fair Selective Classification Via Sufficiency

ICML

Statistical inference for individual fairness

ICLR Machine Learning

Individually Fair Ranking

ICLR AI Fairness

Individually Fair Gradient Boosting

ICLR Machine Learning

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

ICLR Machine Learning

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

AAAI Computer Vision

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

AAAI Machine Learning

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.

AAAI Computer Vision

Learning Task Decomposition with Ordered Memory Policy Network

ICLR

Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning

ICLR Computer Vision

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

ICLR Machine Learning

Hidden Cost of Randomized Smoothing

AISTATS Machine Learning

Neural Network Control Policy Verification with Persistent Adversarial Perturbations

ICML Machine Learning

Fine-grained Angular Contrastive Learning with Coarse Labels

CVPR Computer Vision

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

ECCV Computer Vision

Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions

ICML

Why Do These Match? Explaining the Behavior of Image Similarity Models

ECCV Computer Vision

Self-Progressing Robust Training

AAAI Machine Learning

The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models

CVPR Computer Vision

Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules

CVPR Computer Vision

Separating Skills and Concepts for Novel Visual Question Answering

CVPR

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation

AISTATS Machine Learning

Parameter-Efficient Transfer Learning with Diff Pruning

Computation and Language ACL

Sequence-Level Mixed Sample Data Augmentation

EMNLP Computation and Language

Generating Adversarial Computer Programs using Optimized Obfuscations

ICLR Machine Learning

On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning

ICLR Machine Learning

Robust Overfitting may be mitigated by properly learned smoothening

ICLR

Ordering-based causal structure learning in the presence of latent variables

AISTATS Statistics

Causal structure discovery from distributions arising from mixtures of DAGs

ICML Machine Learning

Online Optimal Control with Affine Constraints

AAAI

A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving

AAAI Artificial Intelligence

RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices

AAAI Machine Learning

Lite Transformer with Long-Short Range Attention

ICLR Computation and Language

GAN Compression: Efficient Architectures for Interactive Conditional GANs

CVPR Computer Vision

Wasserstein Style Transfer

AISTATS Machine Learning

Unsupervised Hierarchical Matching with Optimal Transport over Hyperbolic Spaces

AISTATS

Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

AAAI

Nano-Material Configuration Design with Deep Surrogate Langevin Dynamics

ICLR

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

AAAI Machine Learning

Understanding Behavior of Clinical Models under Domain Shifts

Machine Learning Artificial Intelligence

Fashion IQ: A New Dataset towards Retrieving Images by Natural Language Feedback

CVPR Computer Vision

StarNet: towards weakly supervised few-shot detection and explainable few-shot classification

AAAI Computer Vision

Do GANs always have Nash equilibria?

ICML

Two Simple Ways to Learn Individual Fairness Metrics from Data

ICML Machine Learning

Semi-Supervised Action Recognition with Temporal Contrastive Learning

CVPR Computer Vision

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Computation and Language Machine Learning

Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning

CVPR Computer Vision

Non-Adversarial Video Synthesis with Learned Priors

CVPR Computer Vision

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

AAAI Computer Vision

Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning

ICLR

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

ECCV Computer Vision

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

ECCV

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

AAAI Machine Learning

Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models

Machine Learning Social Networks

Linear Mode Connectivity and The Lottery Ticket Hypothesis

ICML Machine Learning

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

ICML Machine Learning

Curvature-corrected learning dynamics in deep neural networks

ICML

Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing

ICML Machine Learning

Model Fusion with Kullback–Leibler Divergence

ICML

Polygonal Building Extraction by Frame Field Learning

CVPR

Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions

CVPR Computer Vision

Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition

CVPR Computer Vision

Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision

ICML

Leveraging Language to Learn Program Abstractions and Search Heuristics

ICML

Correlation Clustering in Constant Many Parallel Rounds

ICML

A Targeted Assessment of Incremental Processing in Neural Language Models and Humans

ACL Natural Language Processing

Lexicon Learning for Few-Shot Neural Sequence Modeling

ACL Linguistics

Structural Guidance for Transformer Language Models

ACL Natural Language Processing

On Sample Based Explanation Methods for NLP: Efficiency, Faithfulness, and Semantic Evaluation

ACL Natural Language Processing

MSRP Industry Night: Career Exploration with IBM

Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach

ICLR

FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations

ICLR

The Algonauts Project 2021 Challenge: How the Human Brain Makes Sense of a World in Motion

Computational neuroscience Computer Vision

On sensitivity of meta-learning to support data

NeurIPS

Tune It the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density

ICCV

Learning Cross-Modal Contrastive Features for Video Domain Adaptation

ICCV

CDS: Cross-domain self-supervised pre-training

ICCV

Curious Representation Learning for Embodied Intelligence

ICCV

LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision

ICCV

Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting

ICCV

Multimodal Clustering Networks for Self-Supervised Learning From Unlabeled Videos

ICCV

Detector-Free Weakly Supervised Grounding by Separation

ICCV

CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

ICCV

A Broad Study on the Transferability of Visual Representations With Contrastive Learning

ICCV

SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-Powered Intelligent PhlatCam

ICCV

Dynamic Video Quantization for Efficient Inference

ICCV ICCV

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition

ICCV Multimodal Learning

Post-processing for Individual Fairness

NeurIPS

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding

Computer Vision Computational neuroscience

Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models

EMNLP

How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction

EMNLP

Adversarial Attack Generation Empowered by Min-Max Optimization

NeurIPS

Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing

NeurIPS

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks

NeurIPS

Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data

NeurIPS

Learning with Algorithmic Supervision via Continuous Relaxations

NeurIPS

On the Equivalence between Neural Network and Support Vector Machine

NeurIPS

OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization

NeurIPS

Targeted Neural Dynamical Modeling

NeurIPS

TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up

NeurIPS

When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?

NeurIPS

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks

NeurIPS

Look at What I’m Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos

NeurIPS

CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks

NeurIPS

Robust Deep Reinforcement Learning through Adversarial Loss

NeurIPS

Understanding Interlocking Dynamics of Cooperative Rationalization

NeurIPS

PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning

NeurIPS

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception

NeurIPS

Memory-efficient Patch-based Inference for Tiny Deep Learning

NeurIPS

Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language

NeurIPS

3DP3: 3D Scene Perception via Probabilistic Programming

NeurIPS

Measuring Generalization with Optimal Transport

NeurIPS

PARP: Prune Once, Adjust and Re-Prune for Self-Supervised Speech Recognition

NeurIPS

Sequence-to-Sequence Learning with Latent Neural Grammars

NeurIPS

Sliced Mutual Information: A Scalable Measure of Statistical Dependence

NeurIPS

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

NeurIPS

STAR: A Benchmark for Situated Reasoning in Real-World Videos

NeurIPS

Unsupervised Domain Generalization by Learning a Bridge Across Domains

CVPR

Everything at Once – Multi-modal Fusion Transformer for Video Retrieval

CVPR

IA-RED^2 : Interpretability-Aware Redundancy Reduction for Vision Transformers

NeurIPS

Noether networks: meta-learning useful conserved quantities

NeurIPS

Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning

NeurIPS

PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators

NeurIPS

Change Point Detection via Multivariate Singular Spectrum Analysis

NeurIPS

An Exact Characterization of the Generalization Error for the Gibbs Algorithm

NeurIPS

Grammar-Based Grounded Lexicon Learning

NeurIPS

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark

NeurIPS

Learning to Delegate for Large-scale Vehicle Routing

NeurIPS

Efficient Generalization with Distributionally Robust Learning

NeurIPS

Object DGCNN: 3D Object Detection using Dynamic Graphs

NeurIPS

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics

NeurIPS

A large-scale benchmark for few-shot program induction and synthesis

ICML

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time

NeurIPS

Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization

NeurIPS

Discovering State and Action Abstractions for Generalized Task and Motion Planning

AAAI

Temporal and Object Quantification Networks

IJCAI

Reinforcement Learning for Classical Planning: Viewing Heuristics As Dense Reward Generators

ICAPS

Few-Shot Bayesian Imitation Learning with Logical Program Policies

AAAI

Learning Symbolic Operators for Task and Motion Planning

Robotics

CAMPS: Learning Context Specific Abstraction for Efficient Planning in Factored MDPs

CoRL Robotics

GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling

AAAI

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks

AAAI

Reverse Engineering of Imperceptible Adversarial Image Perturbations

ICLR

Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge

AISTATS

Measuring the robustness of Gaussian processes to kernel choice

AISTATS

Regret, stability & fairness in matching markets with bandit learners

AISTATS

A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality

AISTATS Transfer Learning

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series

ICLR

Natural Language Descriptions of Deep Visual Features

ICLR

DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools

ICLR

Controlling Directions Orthogonal to a Classifier

ICLR

Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics

ICLR

Monotonic Differentiable Sorting Networks

ICLR

Linking Emergent and Natural Languages via Corpus Transfer

ICLR

Topological Experience Replay

ICLR

RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation

ICLR

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

ICLR

Optimizer Amalgamation

ICLR

How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis

ICLR

ComPhy: Compositional Physical Reasoning of Objects and Events from Videos

ICLR

Multi-Critic Actor Learning: Teaching RL Policies to Act with Style

ICLR

Network Augmentation for Tiny Deep Learning

ICLR

Extending the WILDS Benchmark for Unsupervised Adaptation

ICLR

Combinatorial Scientific Discovery: Finding New Concept Combinations Beyond Link Prediction

ICLR

Neural Parameter Allocation Search

ICLR

Overcoming The Spectral Bias of Neural Value Approximation

ICLR

Bi-linear Value Networks for Multi-goal Reinforcement Learning

ICLR

AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning

ICLR Reinforcement Learning

RegionViT: Regional-to-Local Attention for Vision Transformers

ICLR

Can an Image Classifier Suffice For Action Recognition?

ICLR

Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations

ICLR

Data-Efficient Graph Grammar Learning for Molecular Generation

ICLR

Adversarial Support Alignment

ICLR

Cross-Modal Discrete Representation Learning

Computer Vision ACL

Is Policy Learning Overrated?: Width-Based Planning and Active Learning for Atari

ICAPS

Beyond Fairness: Reparative Algorithms to Address Historical Injustices of Housing Discrimination in the US

ACM FAccT ACM FAccT

Disentangling Visual and Written Concepts in CLIP

CVPR

LitePose: Efficient Architecture Design for 2D Human Pose Estimation

CVPR

AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation

CVPR

Fixing Malfunctional Objects With Learned Physical Simulation and Functional Prediction

CVPR

Targeted Supervised Contrastive Learning for Long-Tailed Recognition

CVPR

SimVQA: Exploring Simulated Environments for Visual Question Answering

CVPR

Finding Fallen Objects Via Asynchronous Audio-Visual Integration

CVPR

Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data

CVPR

VALHALLA: Visual Hallucination for Machine Translation

CVPR

DeepCurrents: Learning Implicit Representations of Shapes With Boundaries

CVPR

ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes

CVPR

Virtual Correspondence: Humans as a Cue for Extreme-View Geometry

CVPR

A path to AI impact

AI for Good

Fast Convergence for Unstable Reinforcement Learning Problems by Logarithmic Mapping

ICML

On Convergence of Gradient Descent Ascent: A Tight Local Analysis

ICML

Data-Efficient Double-Win Lottery Tickets from Robust Pre-training

ICML

CONTENTVEC: An Improved Self-Supervised Speech Representation by Disentangling Speakers

ICML

Prompting Decision Transformer for Few-shot Policy Generalization

ICML

Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets

ICML

Selective Regression under Fairness Criteria

ICML

Entropic Causal Inference: Graph Identifiability

ICML

Differentiable Top-k Classification Learning

ICML

Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity

ICML

Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework

ICML

Inductive Link Prediction Using Hyper-Relational Facts

IJCAI

Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations

IJCAI

An Adversarial Framework for Generating Unseen Images by Activation Maximization

AAAI

Music Gesture for Visual Sound Separation

Boston-area undergraduates develop a taste for careers in tech at Break Through Tech AI

AI for Good

Contrastive Learning with Complex Heterogeneity

KDD Data Science

Context-Specific Representation Abstraction for Deep Option Learning

AAAI

Outlier impact characterization for time series data

Explainability AAAI

Expanding the MIT-IBM Watson AI Lab’s network of neurons

Entrepreneurship AI for Good

A unified framework for domain adaptive pose estimation

ECCV

A broad study of pre-training for domain generalization and adaptation

ECCV

Self-supervised classification network

ECCV

SNAKE: Shape-aware Neural 3D Keypoint Field

NeurIPS

How hard are computer vision datasets? Calibrating dataset difficulty to viewing time

Computer Vision NeurIPS

On-Device Training Under 256KB Memory

NeurIPS

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting

NeurIPS

Procedural Image Programs for Representation Learning

NeurIPS

Influencing Long-Term Behavior in Multiagent Reinforcement Learning

NeurIPS

FETA: Towards Specializing Foundation Models for Expert Task Applications

NeurIPS

Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens

Computer Vision NeurIPS

k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension

NeurIPS

Faster Linear Algebra for Distance Matrices

NeurIPS

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

NeurIPS

Redeeming Intrinsic Rewards via Constrained Optimization

NeurIPS Optimization

Learning Physical Dynamics with Subequivariant Graph Neural Networks

NeurIPS

Convergent representations of computer programs in human and artificial neural networks

NeurIPS Neuroscience

Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees

NeurIPS

Domain Adaptation meets Individual Fairness. And they get along

NeurIPS AI Fairness

Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing

NeurIPS

DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations

NeurIPS

Factored Adaptation for Non-stationary Reinforcement Learning

NeurIPS Reinforcement Learning

Deep Differentiable Logic Gate Networks

NeurIPS

Advancing Model Pruning via Bi-level Optimization

NeurIPS Optimization

S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint

NeurIPS Computer Vision

The Missing Invariance Principle found — the Reciprocal Twin of Invariant Risk Minimization

NeurIPS

Fairness Reprogramming

NeurIPS AI Fairness

Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing

NeurIPS

Learning Active Camera for Multi-Object Navigation

NeurIPS

Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation

NeurIPS

Learning Neural Acoustic Fields

NeurIPS

3D Concept Grounding on Neural Fields

NeurIPS

How Transferable are Video Representations Based on Synthetic Data?

NeurIPS

3 Questions: Innovation in financial services through synthetic data

AI in Finance Synthetic Data

Personalized Dialogue Generation with Persona-Adaptive Attention

AAAI

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization

AAAI

Zero-shot linear combinations of grounded social interactions with Linear Social MDPs

AAAI

Post-hoc Uncertainty Learning using a Dirichlet Meta-Model

AAAI

DAG-GNN: DAG Structure Learning with Graph Neural Networks

ICML

A Family of Robust Stochastic Operators for Reinforcement Learning

NeurIPS

Temperature Schedules for self-supervised contrastive methods on long-tail data

ICLR

Who Should Predict? Exact Algorithms For Learning to Defer to Humans

AI in Healthcare

Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier

AISTATS AI in Healthcare

Planning with Large Language Models for Code Generation

ICLR

Understanding new tasks through the lens of training data via exponential tilting

ICLR

A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity

ICLR

Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks

ICLR

TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization

ICLR

Hyper-Decision Transformer for Efficient Online Policy Adaptation

ICLR

What Is Missing in IRM Training and Evaluation? Challenges and Solutions

ICLR

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness

ICLR

DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics

ICLR

SoftZoo: A Soft Robot Co-design Benchmark For Locomotion In Diverse Environments

ICLR

ISAAC Newton: Input-based Approximate Curvature for Newton’s Method

ICLR

Contrastive Audio-Visual Masked Autoencoder

ICLR

FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation

ICLR

Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning

ICLR

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

ICLR

PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification

ICLR

Learning to Grow Pretrained Models for Efficient Transformer Training

ICLR

Label-free Concept Bottleneck Models

ICLR

AnyDA: Anytime Domain Adaptation

ICLR

Sampling with Mollified Interaction Energy Descent

ICLR

Learning Proximal Operators to Discover Multiple Optima

ICLR

Is conditional generative modeling all you need for decision-making?

ICLR

Creating space for the evolution of generative and trustworthy AI

Generative Models AI for Good

CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning

CVPR

Teaching Structured Vision & Language Concepts to Vision & Language Models

CVPR

Visual Dependency Transformers: Dependency Tree Emerges from Reversed Attention

CVPR

3D Concept Learning and Reasoning from Multi-View Images

CVPR

Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners

CVPR

Physics-Driven Diffusion Models for Impact Sound Synthesis from Videos

CVPR

Learning Situation Hyper-Graphs for Video Question Answering

CVPR

EC^2 : Emergent Communication for Embodied Control

CVPR

Masked Motion Encoding for Self-Supervised Video Representation Learning

CVPR

FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer

CVPR

SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer

CVPR

Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models

CVPR

Video Test-Time Adaptation for Action Recognition

CVPR

Understanding and Improving Visual Prompting: A Label-Mapping Perspective

CVPR

ConStruct-VL: Data-Free Continual Structured VL Concepts Learning

CVPR

Predicate Invention for Bilevel Planning

AAAI

Learning Rational Subgoals from Demonstrations and Instructions

AAAI

MaskSketch: Unpaired Structure-guided Masked Image Generation

CVPR

Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval

CVPR

Bias Mimicking: A Simple Sampling Approach for Bias Mitigation

CVPR

Language-Guided Audio-Visual Source Separation via Trimodal Consistency

CVPR

TGRL: Teacher Guided Reinforcement Learning Algorithm for POMDPs

ICLR

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

ICML

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

ICML

Change is Hard: A Closer Look at Subpopulation Shift

ICML

Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

ICML

PromptBoosting: Black-Box Text Classification with Ten Forward Passes

ICML

A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening

ICML

Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data

ICML

GC-Flow: A Graph-Based Flow Network for Effective Clustering

ICML

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries

ICML

ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction

ICML

Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

ICML