Papers + Code - MIT-IBM Watson AI Lab

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

Entrepreneurship AI for Good

Outlier impact characterization for time series data

Explainability AAAI

Context-Specific Representation Abstraction for Deep Option Learning

AAAI

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

AI for Good

Music Gesture for Visual Sound Separation

An Adversarial Framework for Generating Unseen Images by Activation Maximization

AAAI

A path to AI impact

AI for Good

Reverse Engineering of Imperceptible Adversarial Image Perturbations

ICLR

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

AAAI

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

AAAI

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

CoRL Robotics

Learning Symbolic Operators for Task and Motion Planning

Robotics

Few-Shot Bayesian Imitation Learning with Logical Program Policies

AAAI

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

ICAPS

Temporal and Object Quantification Networks

IJCAI

Discovering State and Action Abstractions for Generalized Task and Motion Planning

AAAI

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

NeurIPS

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

NeurIPS

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

ICML

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

CVPR

Unsupervised Domain Generalization by Learning a Bridge Across Domains

CVPR

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

NeurIPS

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

NeurIPS

Sliced Mutual Information: A Scalable Measure of Statistical Dependence

NeurIPS

Sequence-to-Sequence Learning with Latent Neural Grammars

NeurIPS

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

NeurIPS

Measuring Generalization with Optimal Transport

NeurIPS

3DP3: 3D Scene Perception via Probabilistic Programming

NeurIPS

A Bayesian Symbolic Approach to Reasoning and Learning in Intuitive Physics

NeurIPS

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

NeurIPS

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

NeurIPS

Memory-efficient Patch-based Inference for Tiny Deep Learning

NeurIPS

Neural Population Geometry Reveals the Role of Stochasticity in Robust Perception

NeurIPS

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

NeurIPS

Understanding Interlocking Dynamics of Cooperative Rationalization

NeurIPS

Robust Deep Reinforcement Learning through Adversarial Loss

NeurIPS

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

NeurIPS

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

NeurIPS

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

NeurIPS

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

NeurIPS

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

NeurIPS

Targeted Neural Dynamical Modeling

NeurIPS

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

NeurIPS

On the Equivalence between Neural Network and Support Vector Machine

NeurIPS

Learning with Algorithmic Supervision via Continuous Relaxations

NeurIPS

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

NeurIPS

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

NeurIPS

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

NeurIPS

Adversarial Attack Generation Empowered by Min-Max Optimization

NeurIPS

Post-processing for Individual Fairness

NeurIPS

Network Augmentation for Tiny Deep Learning

ICLR

On sensitivity of meta-learning to support data

NeurIPS

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

ICLR

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

ICLR

MSRP Industry Night: Career Exploration with IBM

Model Fusion with Kullback–Leibler Divergence

ICML

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

ICML Machine Learning

Curvature-corrected learning dynamics in deep neural networks

ICML

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

ICML Machine Learning

Linear Mode Connectivity and The Lottery Ticket Hypothesis

ICML Machine Learning

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

Machine Learning Social Networks

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

AAAI Machine Learning

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

ECCV Computer Vision

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

ECCV

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

ECCV Computer Vision

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

ICLR

AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition

ICLR Computer Vision

VA-RED^2: Video Adaptive Redundancy Reduction

ICLR Computer Vision

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

AAAI Computer Vision

Non-Adversarial Video Synthesis with Learned Priors

CVPR Computer Vision

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

CVPR Computer Vision

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition

ECCV Computer Vision

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Computation and Language Machine Learning

Semi-Supervised Action Recognition with Temporal Contrastive Learning

CVPR Computer Vision

Two Simple Ways to Learn Individual Fairness Metrics from Data

ICML Machine Learning

Foley Music: Learning to Generate Music from Videos

ECCV Computer Vision

DataMix: Efficient Privacy-Preserving Edge-Cloud Inference

ECCV

A Broader Study of Cross-Domain Few-Shot Learning

ECCV Computer Vision

OnlineAugment: Online Data Augmentation with Less Domain Knowledge

ECCV Computer Vision

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

ECCV Computer Vision

Do GANs always have Nash equilibria?

ICML

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

ECCV Computer Vision

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

CVPR Computer Vision

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

AAAI Computer Vision

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

ECCV Computer Vision

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

CVPR Computer Vision

Understanding Behavior of Clinical Models under Domain Shifts

Machine Learning Artificial Intelligence

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

AAAI Machine Learning

Nano-Material Configuration Design with Deep Surrogate Langevin Dynamics

ICLR

Heterogeneous Knowledge Transfer via Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning

AAAI

Unsupervised Hierarchical Matching with Optimal Transport over Hyperbolic Spaces

AISTATS

Wasserstein Style Transfer

AISTATS Machine Learning

GAN Compression: Efficient Architectures for Interactive Conditional GANs

CVPR Computer Vision

Lite Transformer with Long-Short Range Attention

ICLR Computation and Language

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

AAAI Machine Learning

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

CVPR Computer Vision

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

AAAI Artificial Intelligence

Online Optimal Control with Affine Constraints

AAAI

Causal structure discovery from distributions arising from mixtures of DAGs

ICML Machine Learning

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

AISTATS Statistics

Robust Overfitting may be mitigated by properly learned smoothening

ICLR

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

ICLR Machine Learning

Generating Adversarial Computer Programs using Optimized Obfuscations

ICLR Machine Learning

Sequence-Level Mixed Sample Data Augmentation

EMNLP Computation and Language

Parameter-Efficient Transfer Learning with Diff Pruning

Computation and Language

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation

AISTATS Machine Learning

Separating Skills and Concepts for Novel Visual Question Answering

CVPR

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

CVPR Computer Vision

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

CVPR Computer Vision

Self-Progressing Robust Training

AAAI Machine Learning

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

ECCV Computer Vision

Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions

ICML

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

ECCV Computer Vision

Fine-grained Angular Contrastive Learning with Coarse Labels

CVPR Computer Vision

Neural Network Control Policy Verification with Persistent Adversarial Perturbations

ICML Machine Learning

Hidden Cost of Randomized Smoothing

AISTATS Machine Learning

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics.

ICLR Machine Learning

Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning

ICLR Computer Vision

Learning Task Decomposition with Ordered Memory Policy Network

ICLR

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.

AAAI Computer Vision

Augmenting Policy Learning with Routines Discovered from a Demonstration

AAAI Machine Learning

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

AAAI Computer Vision

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

ICLR Machine Learning

Individually Fair Gradient Boosting

ICLR Machine Learning

Individually Fair Rankings

ICLR AI Fairness

Statistical inference for individual fairness

ICLR Machine Learning

Fair Selective Classification Via Sufficiency

ICML

Black-box Explanation of Object Detectors via Saliency Maps

CVPR Computer Vision

Anycost GANs for Interactive Image Synthesis and Editing

CVPR Computer Vision

Learning-based Support Estimation In Sublinear Time

ICLR

Complementary Evidence Identification in Open-Domain Question Answering

EACL Computation and Language

AGENT: A Benchmark for Core Psychological Reasoning

ICML Artificial Intelligence

Global Prosody Style Transfer Without Text Transcriptions

ICML

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

ICML

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

ICML

Outlier-Robust Optimal Transport

ICML

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

EMNLP Computation and Language

Multilingual BERT Post-Pretraining Alignment

NAACL Computation and Language

Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations

NAACL Computation and Language

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

TACL Computation and Language

Adversarial Option-Aware Hierarchical Imitation Learning

ICML Machine Learning

Dense Associative Memory for Pattern Recognition

NeurIPS Neural and Evolutionary Computing

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

ICML Machine Learning

Large Associative Memory Problem in Neurobiology and Machine Learning

ICLR

Can a Fruit Fly Learn Word Embeddings?

ICLR Computation and Language

Do Neural Networks Really Need to Be So Big?

Efficient AI Deep Learning

The Computational Limits of Deep Learning

Efficient AI Deep Learning

Black Loans Matter: Fighting Bias for AI Fairness in Lending

AI Fairness AI in Finance

Learning Physical Graph Representations from Visual Scenes

NeurIPS

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

NeurIPS

Testing Determinantal Point Processes

NeurIPS

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

NeurIPS

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

NeurIPS

Active Structure Learning of Causal DAGs via Directed Clique Trees

Causal Inference

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

NeurIPS

Online Bayesian Goal Inference for Boundedly-Rational Planning Agents

NeurIPS

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth

NeurIPS

Robust Federated Learning: The Case of Affine Distribution Shifts

Federated Learning

Differentiable Augmentation for Data-Efficient GAN Training

Optimization

Learning Restricted Boltzmann Machines With Sparse Latent Variables

NeurIPS

Debiased Contrastive Learning

NeurIPS

Higher-Order Certification For Randomized Smoothing

Optimization

Entropic Causal Inference: Identifiability and Finite Sample Results

Causal Inference

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

Causal Inference

Applications of Common Entropy in Causal Inference

Causal Inference

Training Stronger Baselines for Learning to Optimize

Optimization

Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance

Bayesian Modeling

Simulating a Primate Visual Cortex at the Front of CNNs Improves Robustness to Adversarial Attacks and Image Corruptions

Neuroscience

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

NeurIPS

Auxiliary Task Reweighting for Minimum-data Learning

NeurIPS

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

Efficient AI

Continuous Regularized Wasserstein Barycenters

Optimal Transport

The Lottery Ticket Hypothesis for the Pre-trained BERT Networks

Efficient AI

Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes

NeurIPS

Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation

NeurIPS

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

Computer Vision Multimodal Learning

Approximate Cross-Validation for Structured Models

Bayesian Modeling

MCUNet: Tiny Deep Learning on IoT Devices

Deep Learning Efficient AI

Universal Domain Adaptation through Self Supervision

Transfer Learning Unsupervised Learning

Does enforcing fairness mitigate biases caused by subpopulation shift?

NeurIPS

Bio-Inspired Hashing for Unsupervised Similarity Search

ICML Neuroscience

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

Cybersecurity Adversarial Machine Learning

SenSR: the first practical algorithm for individual fairness

AI Fairness Robustness

Why Gradient Clipping accelerates training for neural networks

Optimization Efficient AI

CLEVRER: The first video dataset for neuro-symbolic reasoning

Neuro-Symbolic AI Computer Vision

Fast and efficient black-box testing for AI cybersecurity

Cybersecurity Robustness

Learning to learn with distributional signatures for text data

Natural Language Processing Transfer Learning

Layer-wise federated learning with FedMA

Federated Learning

Learning Rate Rewinding for elegant neural network pruning

Efficient AI Deep Learning

Generative Ratio Matching Networks

Generative Models Deep Learning

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

Reinforcement Learning Optimization

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

Efficient AI ICLR

Deep Audio Priors Emerge From Harmonic Convolutional Networks

Audio Processing Deep Learning

A Closer Look at Deep Policy Gradients

Optimization ICLR

Deep Symbolic Superoptimization Without Human Knowledge

Neuro-Symbolic AI Optimization

Reshaping Diverse Planning

Automated Planning

Adversarial Robustness vs Model Compression, or Both?

Robustness

Point-Voxel CNN for Efficient 3D Deep Learning

Efficient AI Deep Learning

CASTER: An AI framework for preventing adverse reactions to medication

AI in Healthcare AAAI

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

Optimization Robustness

Reasoning about Human-Object Interactions through Dual Attention Networks

Computer Vision

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

Sentence Embedding Alignment for Lifelong Relation Extraction

Natural Language Processing Lifelong Learning

Moments in Time Dataset: one million videos for event understanding

Computer Vision Multimodal 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 Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Optimization

Online AI planning with graph neural networks and adaptive scheduling

Automated Planning Graph Deep Learning

Reading between the lines with graph deep learning for NLP

Natural Language Processing AAAI

A unifying framework for expectation-aware AI planning

Automated Planning

A content-aware attack generator for AI cybersecurity

Adversarial Machine Learning Cybersecurity

Automating machine learning with a joint selection framework

AutoML Efficient AI

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph Deep Learning AAAI

Embedding Compression with Isotropic Iterative Quantization

Natural Language Processing

Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference

Deep Learning Bayesian Modeling

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

Optimization NeurIPS

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

Computer Vision

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

Alleviating label switching with optimal transport

Optimal Transport

Visual Concept-Metaconcept Learning

Neuro-Symbolic AI

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

Causal Inference

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

Natural Language Processing Deep Rationalization

New tricks from old dogs: multi-source transfer learning

Transfer Learning Explainability

Reverse-engineering causal graphs with soft interventions

Causal Inference

SimVAE: Simulator-Assisted Training for Interpretable Generative Models

Generative Models Explainability

Cross-channel Communication Networks

Deep Learning Computer Vision

The Future of Work: How New Technologies Are Transforming Tasks

Future of Work

Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference

Lifelong Learning Transfer Learning

Seeing What a GAN Cannot Generate

Generative Models

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

Computer Vision

Defensive Quantization: When Efficiency Meets Robustness

Efficient AI Robustness

Local Unsupervised Learning for Image Analysis

Unsupervised Learning Computer Vision

Neural language models as psycholinguistic subjects: Representations of syntactic state

Natural Language Processing Time Series

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

Computer Vision Time Series

Deep Leakage from Gradients

Robustness Deep Learning

Write, Execute, Assess: Program Synthesis with a REPL

Program Synthesis

Variational Russian Roulette for Deep Bayesian Nonparametrics

Deep Learning Bayesian Modeling

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

Graph Deep Learning Natural Language Processing

Bayesian Nonparametric Federated Learning of Neural Networks

Federated Learning

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

Neuro-Symbolic AI Computer Vision

Unsupervised learning by competing hidden units

PNAS Unsupervised Learning

Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

Computer Vision

Structural Supervision Improves Learning of Non-Local Grammatical Dependencies

Natural Language Processing

Tight Certificates of Adversarial Robustness

Cybersecurity NeurIPS

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach

ICML

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

Robustness

Weakly Supervised Dense Event Captioning in Videos

Computer Vision

Neural Network Robustness Certification with General Activation Functions

Robustness Deep Learning

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

AI in Finance Graph Deep Learning

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

Robustness

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Generative Models Explainability

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

Multi-agent Systems

Unsupervised learning with contrastive latent variable models

Unsupervised Learning

Co-regularized Alignment for Unsupervised Domain Adaptation

Transfer Learning Deep Learning

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

Computer Vision Time Series

Experimental Design for Cost-Aware Learning of Causal Graphs

Causal Inference

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

AI in Healthcare Deep Learning

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

Neuro-Symbolic AI Computer Vision

signSGD via Zeroth-Order Oracle

Optimization Robustness

Learning Entropic Wasserstein Embeddings

Machine Learning Optimal Transport

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

Generative Models Graph Deep Learning

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

AI in Healthcare Natural Language Processing

Deriving Machine Attention from Human Rationales

Deep Rationalization Natural Language Processing

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

Generative Models

Structured Adversarial Attack: Towards General Implementation and Better Interpretability

Robustness Explainability

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

Computer Vision Few-shot Learning

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

Robustness Optimization

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization

Optimization Deep Learning

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

Computer Vision Generative Models

Dialog-based Interactive Image Retrieval

Computer Vision

Learning to Teach in Cooperative Multiagent Reinforcement Learning

Multi-agent Systems Reinforcement Learning

The Sound of Pixels

Multimodal Learning Computer Vision

Learning to Separate Object Sounds by Watching Unlabeled Video

Computer Vision

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Efficient AI Deep Learning

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

Robustness Natural Language Processing

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

BlockDrop: Dynamic Inference Paths in Residual Networks

Computer Vision

Action Centered Contextual Bandits

Deep Learning

Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Causal Inference

Gradient Descent for Spiking Neural Networks

Deep Learning

Ensemble Estimation of Information Divergence

Information Theory