NeurIPS 2022

2,834 papers

Measuring Data Reconstruction Defenses in Collaborative Inference Systems

Mengda Yang, Ziang Li, Juan Wang, Hongxin Hu, Ao Ren

NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos

Yi-Ling Qiao, Alexander Gao, Ming Lin

Learning Equivariant Segmentation with Instance-Unique Querying

Wenguan Wang, James Liang, Dongfang Liu

Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds

Joshua Albrecht, Abraham Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski

Causally motivated multi-shortcut identification and removal

Jiayun Zheng, Maggie Makar

Verification and search algorithms for causal DAGs

Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya

Learning to Constrain Policy Optimization with Virtual Trust Region

Thai Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do

Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization

Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A Osborne

Neural Circuit Architectural Priors for Embodied Control

Nikhil Bhattasali, Anthony M Zador, Tatiana Engel

Data Augmentation MCMC for Bayesian Inference from Privatized Data

Nianqiao Ju, Jordan Awan, Ruobin Gong, Vinayak Rao

Scalable Neural Video Representations with Learnable Positional Features

Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin

Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations

Fukun Yin, Wen Liu, Zilong Huang, Pei Cheng, Tao Chen

Differentially Private Linear Sketches: Efficient Implementations and Applications

Fuheng Zhao, Dan Qiao, Rachel Redberg, Divyakant Agrawal, Amr El Abbadi

FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting

Tian Zhou, Ziqing MA, xue wang, Qingsong Wen, Liang Sun

Training Spiking Neural Networks with Local Tandem Learning

Qu Yang, Jibin Wu, Malu Zhang, Yansong Chua, Xinchao Wang

ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler

Jiaxin Zhang, Yashar Moshfeghi

Sampling from Log-Concave Distributions with Infinity-Distance Guarantees

Oren Mangoubi, Nisheeth Vishnoi

Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning

Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang, haiyin piao

Masked Autoencoding for Scalable and Generalizable Decision Making

Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel

Teacher Forcing Recovers Reward Functions for Text Generation

Yongchang Hao, Yuxin Liu, Lili Mou

Monte Carlo Tree Descent for Black-Box Optimization

Yaoguang Zhai, Sicun Gao

Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization

Stefan Stojanov, Anh Thai, Zixuan Huang, James M. Rehg

The Neural Testbed: Evaluating Joint Predictions

Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu

Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels

Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland

Interaction-Grounded Learning with Action-Inclusive Feedback

Tengyang Xie, Akanksha Saran, Dylan J Foster, Lekan Molu, Ida Momennejad

Learning Energy Networks with Generalized Fenchel-Young Losses

Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Leonard Hussenot, Matthieu Geist

Improving Policy Learning via Language Dynamics Distillation

Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel

OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters

Piera Riccio, Bill Psomas, Francesco Galati, Francisco Escolano, Thomas Hofmann

EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL

Thomas Carta, Pierre-yves Oudeyer, Olivier Sigaud, Sylvain Lamprier

QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query

Yabo Xiao, Kai Su, Xiaojuan Wang, Dongdong Yu, Lei Jin

Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations

Alexander Immer, Tycho van der Ouderaa, Gunnar Rätsch, Vincent Fortuin, Mark van der Wilk

Unsupervised Object Detection Pretraining with Joint Object Priors Generation and Detector Learning

Yizhou Wang, Meilin Chen, SHIXIANG TANG, Feng Zhu, Haiyang Yang

Anonymous Bandits for Multi-User Systems

Hossein Esfandiari, Vahab Mirrokni, Jon Schneider

Modular Flows: Differential Molecular Generation

Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg

Sparse Fourier Backpropagation in Cryo-EM Reconstruction

Dari Kimanius, Kiarash Jamali, Sjors Scheres

NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks

Renbo Tu, Nicholas Roberts, Misha Khodak, Junhong Shen, Frederic Sala

Decision Trees with Short Explainable Rules

Victor Feitosa Souza, Ferdinando Cicalese, Eduardo Laber, Marco Molinaro

Learning Optimal Flows for Non-Equilibrium Importance Sampling

Yu Cao, Eric Vanden-Eijnden

A Variational Edge Partition Model for Supervised Graph Representation Learning

Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou

Reinforced Genetic Algorithm for Structure-based Drug Design

Tianfan Fu, Wenhao Gao, Connor Coley, Jimeng Sun

AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning

Tao Yang, JInghao Deng, Xiaojun Quan, Qifan Wang, Shaoliang Nie

Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability

Jonathan Crabbe, Alicia Curth, Ioana Bica, Mihaela van der Schaar

I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification

Muhammad Ferjad Naeem, Yongqin Xian, Luc V Gool, Federico Tombari

Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction

Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko

Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits

Junwen Yang, Vincent Tan

Moment Distributionally Robust Tree Structured Prediction

Yeshu Li, Danyal Saeed, Xinhua Zhang, Brian Ziebart, Kevin Gimpel

Intrinsic dimensionality estimation using Normalizing Flows

Christian Horvat, Jean-pascal Pfister

Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions

Weirui Ye, Pieter Abbeel, Yang Gao

Homomorphic Matrix Completion

Xiao-Yang Liu, Zechu (Steven) Li, Xiaodong Wang

Flexible Neural Image Compression via Code Editing

Chenjian Gao, Tongda Xu, Dailan He, Yan Wang, Hongwei Qin

In Defense of the Unitary Scalarization for Deep Multi-Task Learning

Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan K Mudigonda

E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance

Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu

Bayesian Active Learning with Fully Bayesian Gaussian Processes

Christoffer Riis, Francisco Antunes, Frederik Hüttel, Carlos Lima Azevedo, Francisco Pereira

Introspective Learning : A Two-Stage approach for Inference in Neural Networks

Mohit Prabhushankar, Ghassan AlRegib

ULNeF: Untangled Layered Neural Fields for Mix-and-Match Virtual Try-On

Igor Santesteban, Miguel Otaduy, Nils Thuerey, Dan Casas

Does GNN Pretraining Help Molecular Representation?

Ruoxi Sun, Hanjun Dai, Adams Wei Yu

Improved Feature Distillation via Projector Ensemble

Yudong Chen, Sen Wang, Jiajun Liu, Xuwei Xu, Frank de Hoog

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers

Colin Wei, Yining Chen, Tengyu Ma

Dataset Inference for Self-Supervised Models

Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan

Embrace the Gap: VAEs Perform Independent Mechanism Analysis

Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow

Task-Agnostic Graph Explanations

Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward Huang, Nikhil Rao

HandMeThat: Human-Robot Communication in Physical and Social Environments

Yanming Wan, Jiayuan Mao, Josh Tenenbaum

Value Function Decomposition for Iterative Design of Reinforcement Learning Agents

James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan

ViSioNS: Visual Search in Natural Scenes Benchmark

Fermín Travi, Gonzalo Ruarte, Gaston Bujia, Juan Esteban Kamienkowski

AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs

Daniele Zambon, Cesare Alippi

Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech

Ziyue Jiang, Zhe Su, Zhou Zhao, Qian Yang, Yi Ren

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack

Yu Yang, Baharan Mirzasoleiman, Tianyu Liu, Tian Yu Liu

A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval

Hao Li, Jingkuan Song, Lianli Gao, Pengpeng Zeng, Haonan Zhang

Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification

Ruoxi Jiang, Rebecca Willett

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets

Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-jan Kindermans, Madeleine Udell

On the Symmetries of Deep Learning Models and their Internal Representations

Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge

Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning

Hua Wei, Jingxiao Chen, Xiyang Ji, Hongyang Qin, Minwen Deng

Direct Advantage Estimation

Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf

GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations

Enmao Diao, Jie Ding, Vahid Tarokh

A Quadrature Rule combining Control Variates and Adaptive Importance Sampling

Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman

Learning Invariant Graph Representations for Out-of-Distribution Generalization

Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu

Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Template based Graph Neural Network with Optimal Transport Distances

Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty

Capturing Failures of Large Language Models via Human Cognitive Biases

Erik Jones, Jacob Steinhardt

LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks

Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira

A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback

Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus

Qiwen Cui, Simon S Du

Hilbert Distillation for Cross-Dimensionality Networks

Dian Qin, Haishuai Wang, Zhe Liu, HONGJIA XU, Sheng Zhou

Amortized Mixing Coupling Processes for Clustering

Huafeng Liu, Liping Jing

Spatial Mixture-of-Experts

Nikoli Dryden, Torsten Hoefler

Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space

Heng Lian

Evaluating Out-of-Distribution Performance on Document Image Classifiers

Stefan Larson, Yi Yang Gordon Lim, Yutong Ai, David Kuang, Kevin Leach

Zero-Sum Stochastic Stackelberg Games

Denizalp Goktas, Sadie Zhao, Amy Greenwald

Evolution of Neural Tangent Kernels under Benign and Adversarial Training

Noel Loo, Ramin Hasani, Alexander Amini, Daniela Rus

Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference

Richard Grumitt, Biwei Dai, Uros Seljak

MsSVT: Mixed-scale Sparse Voxel Transformer for 3D Object Detection on Point Clouds

Shaocong Dong, Lihe Ding, Haiyang Wang, Tingfa Xu, Xinli Xu

ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection

HUIPING ZHUANG, Zhenyu Weng, Hongxin Wei, RENCHUNZI XIE, Kar-Ann Toh

Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces

Leonard Papenmeier, Luigi Nardi, Matthias Poloczek

Efficient Methods for Non-stationary Online Learning

Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou

Conformalized Fairness via Quantile Regression

Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong

Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold

Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu

S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning

Daesol Cho, Dongseok Shim, H. Jin Kim

Weighted Mutual Learning with Diversity-Driven Model Compression

Miao Zhang, Li Wang, David Campos, Wei Huang, Chenjuan Guo

Provable General Function Class Representation Learning in Multitask Bandits and MDP

Rui Lu, Andrew Zhao, Simon S Du, Gao Huang

Joint Entropy Search For Maximally-Informed Bayesian Optimization

Carl Hvarfner, Frank Hutter, Luigi Nardi