NeurIPS

All Work

An AI model trained on data that looks real but won’t leak personal information
An AI model trained on data that looks real but won’t leak personal information
IBM Research
Automated system teaches users when to collaborate with an AI assistant
Automated system teaches users when to collaborate with an AI assistant
MIT News
New method uses crowdsourced feedback to help train robots
New method uses crowdsourced feedback to help train robots
MIT News
A Family of Robust Stochastic Operators for Reinforcement Learning
A Family of Robust Stochastic Operators for Reinforcement Learning
 
How Transferable are Video Representations Based on Synthetic Data?
How Transferable are Video Representations Based on Synthetic Data?
 
3D Concept Grounding on Neural Fields
3D Concept Grounding on Neural Fields
 
Learning Neural Acoustic Fields
Learning Neural Acoustic Fields
 
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
 
Learning Active Camera for Multi-Object Navigation
Learning Active Camera for Multi-Object Navigation
 
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
 
Fairness Reprogramming
Fairness Reprogramming
 
The Missing Invariance Principle found — the Reciprocal Twin of Invariant Risk Minimization
The Missing Invariance Principle found — the Reciprocal Twin of Invariant Risk Minimization
 
S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint
S3-NeRF: Neural Reflectance Field from Shading and Shadow under a Single Viewpoint
 
Advancing Model Pruning via Bi-level Optimization
Advancing Model Pruning via Bi-level Optimization
 
Deep Differentiable Logic Gate Networks
Deep Differentiable Logic Gate Networks
 
Factored Adaptation for Non-stationary Reinforcement Learning
Factored Adaptation for Non-stationary Reinforcement Learning
 
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
 
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing
 
Domain Adaptation meets Individual Fairness. And they get along
Domain Adaptation meets Individual Fairness. And they get along
 
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees
 
Convergent representations of computer programs in human and artificial neural networks
Convergent representations of computer programs in human and artificial neural networks
 
Learning Physical Dynamics with Subequivariant Graph Neural Networks
Learning Physical Dynamics with Subequivariant Graph Neural Networks
 
Redeeming Intrinsic Rewards via Constrained Optimization
Redeeming Intrinsic Rewards via Constrained Optimization
 
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
 
Faster Linear Algebra for Distance Matrices
Faster Linear Algebra for Distance Matrices
 
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension
k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension
 
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens
 
FETA: Towards Specializing Foundation Models for Expert Task Applications
FETA: Towards Specializing Foundation Models for Expert Task Applications
 
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
 
Procedural Image Programs for Representation Learning
Procedural Image Programs for Representation Learning
 
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting
 
On-Device Training Under 256KB Memory
On-Device Training Under 256KB Memory
 
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
 
SNAKE: Shape-aware Neural 3D Keypoint Field
SNAKE: Shape-aware Neural 3D Keypoint Field
 
Debugging foundation models for bias
Debugging foundation models for bias
IBM Research
A simpler path to better computer vision
A simpler path to better computer vision
MIT News
A far-sighted approach to machine learning
A far-sighted approach to machine learning
MIT News
This AI can harness sound to reveal the structure of unseen spaces
This AI can harness sound to reveal the structure of unseen spaces
Popular Science
Perceptron: AI that sees with sound, learns to walk and predicts seismic physics
Perceptron: AI that sees with sound, learns to walk and predicts seismic physics
TechCrunch
In machine learning, synthetic data can offer real performance improvements
In machine learning, synthetic data can offer real performance improvements
MIT News
Learning on the edge
Learning on the edge
MIT News
TinyML is bringing neural networks to small microcontrollers
TinyML is bringing neural networks to small microcontrollers
TechTalks
Clever Compression of Some Neural Nets Improves Performance
Clever Compression of Some Neural Nets Improves Performance
IEEE Spectrum
AI Researchers Fight Noise by Turning to Biology
AI Researchers Fight Noise by Turning to Biology
Quanta Magazine
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
 
Object DGCNN: 3D Object Detection using Dynamic Graphs
Object DGCNN: 3D Object Detection using Dynamic Graphs
 
Efficient Generalization with Distributionally Robust Learning
Efficient Generalization with Distributionally Robust Learning
 
Learning to Delegate for Large-scale Vehicle Routing
Learning to Delegate for Large-scale Vehicle Routing
 
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
 
Grammar-Based Grounded Lexicon Learning
Grammar-Based Grounded Lexicon Learning
 
An Exact Characterization of the Generalization Error for the Gibbs Algorithm
An Exact Characterization of the Generalization Error for the Gibbs Algorithm
 
Change Point Detection via Multivariate Singular Spectrum Analysis
Change Point Detection via Multivariate Singular Spectrum Analysis
 
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
PerSim: Data-Efficient Offline Reinforcement Learning with Heterogeneous Agents via Personalized Simulators
 
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning
Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning
 
Noether networks: meta-learning useful conserved quantities
Noether networks: meta-learning useful conserved quantities
 
IA-RED^2 : Interpretability-Aware Redundancy Reduction for Vision Transformers
IA-RED^2 : Interpretability-Aware Redundancy Reduction for Vision Transformers
 
Machine learning speeds up vehicle routing
Machine learning speeds up vehicle routing
MIT News
Generating a realistic 3D world
Generating a realistic 3D world
MIT News
Toward speech recognition for uncommon spoken languages
Toward speech recognition for uncommon spoken languages
MIT News
AI Algorithms Are Slimming Down to Fit in Your Fridge
AI Algorithms Are Slimming Down to Fit in Your Fridge
WIRED
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
 
Black Loans Matter: Fighting Bias for AI Fairness in Lending
Black Loans Matter: Fighting Bias for AI Fairness in Lending
 
Researchers Figured Out How to Fit More AI Than Ever onto Internet of Things Microchips
Researchers Figured Out How to Fit More AI Than Ever onto Internet of Things Microchips
Morning Brew
Is neuroscience the key to protecting AI from adversarial attacks?
Is neuroscience the key to protecting AI from adversarial attacks?
TechTalks
Learning Physical Graph Representations from Visual Scenes
Learning Physical Graph Representations from Visual Scenes
 
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
 
Testing Determinantal Point Processes
Testing Determinantal Point Processes
 
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
Fairness in Streaming Submodular Maximization: Algorithms and Hardness
 
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
 
Active Structure Learning of Causal DAGs via Directed Clique Trees
Active Structure Learning of Causal DAGs via Directed Clique Trees
 
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
 
Online Bayesian Goal Inference for Boundedly-Rational Planning Agents
Online Bayesian Goal Inference for Boundedly-Rational Planning Agents
 
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth
 
Robust Federated Learning: The Case of Affine Distribution Shifts
Robust Federated Learning: The Case of Affine Distribution Shifts
 
Differentiable Augmentation for Data-Efficient GAN Training
Differentiable Augmentation for Data-Efficient GAN Training
 
Learning Restricted Boltzmann Machines With Sparse Latent Variables
Learning Restricted Boltzmann Machines With Sparse Latent Variables
 
Debiased Contrastive Learning
Debiased Contrastive Learning
 
Neuroscientists find a way to make object-recognition models perform better
Neuroscientists find a way to make object-recognition models perform better
MIT News
Higher-Order Certification For Randomized Smoothing
Higher-Order Certification For Randomized Smoothing
 
Entropic Causal Inference: Identifiability and Finite Sample Results
Entropic Causal Inference: Identifiability and Finite Sample Results
 
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning
 
Applications of Common Entropy in Causal Inference
Applications of Common Entropy in Causal Inference
 
Training Stronger Baselines for Learning to Optimize
Training Stronger Baselines for Learning to Optimize
 
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance
 
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations
 
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment
 
Auxiliary Task Reweighting for Minimum-data Learning
Auxiliary Task Reweighting for Minimum-data Learning
 
Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning
Tiny Transfer Learning: Towards Memory-Efficient On-Device Learning
 
Continuous Regularized Wasserstein Barycenters
Continuous Regularized Wasserstein Barycenters
 
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
The Lottery Ticket Hypothesis for the Pre-trained BERT Networks
 
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
 
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation
 
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
 
Approximate Cross-Validation for Structured Models
Approximate Cross-Validation for Structured Models
 
MCUNet: Tiny Deep Learning on IoT Devices
MCUNet: Tiny Deep Learning on IoT Devices
 
System brings deep learning to “internet of things” devices
System brings deep learning to “internet of things” devices
MIT News
Does enforcing fairness mitigate biases caused by subpopulation shift?
Does enforcing fairness mitigate biases caused by subpopulation shift?
 
ObjectNet: A bias-controlled dataset object recognition
ObjectNet: A bias-controlled dataset object recognition
 
Point-Voxel CNN for Efficient 3D Deep Learning
Point-Voxel CNN for Efficient 3D Deep Learning
 
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
 
Sobolev Independence Criterion
Sobolev Independence Criterion
 
Private Testing of Distributions via Sample Permutations
Private Testing of Distributions via Sample Permutations
 
Image Synthesis with a Single (Robust) Classifier
Image Synthesis with a Single (Robust) Classifier
 
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks
 
A Game Theoretic Approach to Class-wise Selective Rationalization
A Game Theoretic Approach to Class-wise Selective Rationalization
 
Hierarchical Optimal Transport for Document Representation
Hierarchical Optimal Transport for Document Representation
 
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions
 
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers
 
Statistical Model Aggregation via Parameter Matching
Statistical Model Aggregation via Parameter Matching
 
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement
 
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
 
Adversarial Examples Are Not Bugs, They Are Features
Adversarial Examples Are Not Bugs, They Are Features
 
Sample Efficient Active Learning of Causal Trees
Sample Efficient Active Learning of Causal Trees
 
Scalable inference of topic evolution via models for latent geometric structures
Scalable inference of topic evolution via models for latent geometric structures
 
ZO-AdaMM: Derivative-free optimization for black-box problems
ZO-AdaMM: Derivative-free optimization for black-box problems
 
Cross-channel Communication Networks
Cross-channel Communication Networks
 
Tight Certificates of Adversarial Robustness
Tight Certificates of Adversarial Robustness
 
Learning and Testing Causal Models with Interventions
Learning and Testing Causal Models with Interventions
 
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
 
Direct Estimation of Differences in Causal Graphs
Direct Estimation of Differences in Causal Graphs
 
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction
 
How Does Batch Normalization Help Optimization?
How Does Batch Normalization Help Optimization?
 
HOGWILD!-Gibbs Can Be PanAccurate
HOGWILD!-Gibbs Can Be PanAccurate
 
Efficient Neural Network Robustness Certification with General Activation Functions
Efficient Neural Network Robustness Certification with General Activation Functions
 
Dialog-based Interactive Image Retrieval
Dialog-based Interactive Image Retrieval