Paper Title Authors
A sampling-based circuit for optimal decision making Camille Rullán Buxó · Cristina Savin
Across-animal odor decoding by probabilistic manifold alignment Pedro Herrero-Vidal · Dmitry Rinberg · Cristina Savin
Offline RL Without Off-Policy Evaluation David Brandfonbrener · Will Whitney · Rajesh Ranganath · Joan Bruna
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics Carles Domingo i Enrich · Youssef Mroueh
Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov · Patrick Nicholson · Sanae Lotfi · Andrew Wilson
Conditioning Sparse Variational Gaussian Processes for Online Decision-making Wesley Maddox · Samuel Stanton · Andrew Wilson
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser Zahra Kadkhodaie · Eero P Simoncelli
Bayesian Optimization with High-Dimensional Outputs Wesley Maddox · Maximilian Balandat · Andrew Wilson · Eytan Bakshy
Impression learning: Online representation learning with synaptic plasticity Colin Bredenberg · Benjamin Lyo · Eero P Simoncelli · Cristina Savin
Differentiable Spline Approximations Minsu Cho · Aditya Balu · Ameya Joshi · Anjana Deva Prasad · Biswajit Khara · Soumik Sarkar · Baskar Ganapathysubramanian · Adarsh Krishnamurthy · Chinmay Hegde
On the Cryptographic Hardness of Learning Single Periodic Neurons Min Jae Song · Ilias Zadik · Joan Bruna
Adaptive Denoising via GainTuning Sreyas Mohan · Joshua L Vincent · Ramon Manzorro · Peter Crozier · Carlos Fernandez-Granda · Eero P Simoncelli
Residual Pathway Priors for Soft Equivariance Constraints Marc Finzi · Greg Benton · Andrew Wilson
Does Knowledge Distillation Really Work? Samuel Stanton · Pavel Izmailov · Polina Kirichenko · Alex A Alemi · Andrew Wilson
Inverse-Weighted Survival Games Xintian Han · Mark Goldstein · Aahlad Puli · Thomas Wies · Adler Perotte · Rajesh Ranganath
Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others Kanishk Gandhi · Gala Stojnic · Brenden Lake · Moira R Dillon
Hard-Attention for Scalable Image Classification Athanasios Papadopoulos · Pawel Korus · Nasir Memon
Implicit Sparse Regularization: The Impact of Depth and Early Stopping Jiangyuan Li · Thanh V Nguyen · Chinmay Hegde · Raymond K. W. Wong
Learning Distilled Collaboration Graph for Multi-Agent Perception Yiming Li · Shunli Ren · Pengxiang Wu · Siheng Chen · Chen Feng · Wenjun Zhang
Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning Aakash Kaku · Sahana Upadhya · Narges Razavian
Automatic Data Augmentation for Generalization in Reinforcement Learning Roberta Raileanu · Maxwell Goldstein · Denis Yarats · Ilya Kostrikov · Rob Fergus
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar · David W Hogg · Kate Storey-Fisher · Weichi Yao · Ben Blum-Smith
Circa: Stochastic ReLUs for Private Deep Learning Zahra Ghodsi · Nandan Kumar Jha · Brandon Reagen · Siddharth Garg
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization Clement Gehring · Kenji Kawaguchi · Jiaoyang Huang · Leslie Kaelbling
Maxwell Nye · MH Tessler · Josh Tenenbaum · Brenden Lake
Dynamic Trace Estimation Prathamesh Dharangutte · Christopher Musco
True Few-Shot Learning with Language Models Ethan Perez · Douwe Kiela · Kyunghyun Cho
On the Existence of The Adversarial Bayes Classifier Pranjal Awasthi, Natalie Frank, Mehryar Mohri
Calibration and Consistency of Adversarial Surrogate Losses Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong
Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu
On the Sample Complexity of Learning under Geometric Stability Alberto Bietti, Luca Venturi, Joan Bruna
On the interplay between data structure and loss function in classification problems Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli
Large-Scale Unsupervised Object Discovery Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Perez, Jean Ponce
Hash Layers For Large Sparse Models Stephen Roller · Sainbayar Sukhbaatar · arthur d szlam · Jason Weston
A Biased Graph Neural Network Sampler with Near-Optimal Regret Qingru Zhang · David P Wipf · Quan Gan · Le Song
Controlling Neural Networks with Rule Representations Sungyong Seo · Sercan Arik · Jinsung Yoon · Xiang Zhang · Kihyuk Sohn · Tomas Pfister
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leora Horwitz, David Sontag
Neural Active Learning with Performance Guarantees Zhilei Wang, Pranjal Awasthi, Christoph Dann, Ayush Sekhari, Claudio Gentile
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction Longyuan Li, Jian Yao, Li Kevin Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang
Embedding Principle of Loss Landscape of Deep Neural Networks Yaoyu Zhang, Zhongwang Zhang, Tao Luo, Zhiqin Xu
IRM—when it works and when it doesn’t: A test case of natural language inference Yana Dranker, He He, Yonatan Belinkov
Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II Yossi Arjevani · Michael Field
A Normative and Biologically Plausible Algorithm for Independent Component Analysis Yanis Bahroun, Dmitri Chklovskii, Anirvan M. Sengupta
Neural optimal feedback control with local learning rules Johannes Friedrich, Siavash Golkar, Shiva Farashahi, Alexander Genkin, Anirvan M. Sengupta, Dmitri Chklovskii
Autobahn: Automorphism-based Graph Neural Nets Erik Henning Thiede . Wenda Zhou . Risi Kondor