NeurIPS

Black Loans Matter: Fighting Bias for AI Fairness in Lending

Learning Physical Graph Representations from Visual Scenes

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

Testing Determinantal Point Processes

Fairness in Streaming Submodular Maximization: Algorithms and Hardness

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

Active Structure Learning of Causal DAGs via Directed Clique Trees

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

Online Bayesian Goal Inference for Boundedly-Rational Planning Agents

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth

Robust Federated Learning: The Case of Affine Distribution Shifts

Differentiable Augmentation for Data-Efficient GAN Training

Learning Restricted Boltzmann Machines With Sparse Latent Variables

Debiased Contrastive Learning

Higher-Order Certification For Randomized Smoothing

Entropic Causal Inference: Identifiability and Finite Sample Results

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

Applications of Common Entropy in Causal Inference

Training Stronger Baselines for Learning to Optimize

Asymptotic Guarantees for Generative Modeling based on the Smooth Wasserstein Distance

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

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

Auxiliary Task Reweighting for Minimum-data Learning

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

Continuous Regularized Wasserstein Barycenters

The Lottery Ticket Hypothesis for the Pre-trained BERT Networks

Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes

Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation

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

Approximate Cross-Validation for Structured Models

MCUNet: Tiny Deep Learning on IoT Devices

Universal Domain Adaptation through Self Supervision

ObjectNet: A bias-controlled dataset object recognition

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

Tight Certificates of Adversarial Robustness