NeurIPS 2023

3,540 papers

Coherent Soft Imitation Learning

Joe Watson, Sandy Huang, Nicolas Heess

Fast Model DeBias with Machine Unlearning

Ruizhe Chen, Jianfei Yang, Huimin Xiong, Jianhong Bai, Tianxiang Hu

REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths

Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong

Loss Dynamics of Temporal Difference Reinforcement Learning

Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan

A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment

Yixuan Xu, Steven Jecmen, Zimeng Song, Fei Fang

ARTree: A Deep Autoregressive Model for Phylogenetic Inference

Tianyu Xie, Cheng Zhang

Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition

Yuhang Zhang, Yaqi Li, lixiong Qin, Xuannan Liu, Weihong Deng

BCDiff: Bidirectional Consistent Diffusion for Instantaneous Trajectory Prediction

Rongqing Li, Changsheng Li, Dongchun Ren, Guangyi Chen, Ye Yuan

Improved Frequency Estimation Algorithms with and without Predictions

Anders Aamand, Justin Chen, Huy Nguyen, Sandeep Silwal, Ali Vakilian

ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence

Ben Dai, Yixuan Qiu

Computing a human-like reaction time metric from stable recurrent vision models

Lore Goetschalckx, Lakshmi Narasimhan Govindarajan, Alekh Karkada Ashok, Aarit Ahuja, David Sheinberg

Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power

Junru Zhou, Jiarui Feng, Xiyuan Wang, Muhan Zhang

Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective

Zhiding Liu, Mingyue Cheng, Zhi Li, Zhenya Huang, Qi Liu

Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints

Xinyi Hu, Jasper Lee, Jimmy Lee

Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression

Allan Raventós, Mansheej Paul, Feng Chen, Surya Ganguli

Eliminating Domain Bias for Federated Learning in Representation Space

Jianqing Zhang, Yang Hua, Jian Cao, Hao Wang, Tao Song

ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction

Alfredo De Goyeneche Macaya, Shreya Ramachandran, Ke Wang, Ekin Karasan, Joseph Y. Cheng

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

Vignesh Kothapalli, Tom Tirer, Joan Bruna

Participatory Personalization in Classification

Hailey Joren, Chirag Nagpal, Katherine A. Heller, Berk Ustun

FouriDown: Factoring Down-Sampling into Shuffling and Superposing

Qi Zhu, man zhou, Jie Huang, Naishan Zheng, Hongzhi Gao

SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

Taesik Gong, Yewon Kim, Taeckyung Lee, Sorn Chottananurak, Sung-Ju Lee

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method

Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Matthew Le, Apoorv Vyas, Bowen Shi, Brian Karrer, Leda Sari

StEik: Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation

Huizong Yang, Yuxin Sun, Ganesh Sundaramoorthi, Anthony Yezzi

FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing

Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren, Lei Yang

URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates

Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Dr. Enkelejda Kasneci

Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models

Naman Deep Singh, Francesco Croce, Matthias Hein

Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture

Galen Pogoncheff, Jacob Granley, Michael Beyeler

A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications

Yanbo Chen, Weiwei Liu

DSR: Dynamical Surface Representation as Implicit Neural Networks for Protein

Daiwen Sun, He Huang, Yao Li, Xinqi Gong, Qiwei Ye

Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis

Zhu Wang, Sourav Medya, Sathya Ravi

Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners

Rachel Redberg, Antti Koskela, Yu-Xiang Wang

Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning

Yang Yang, Yuxuan Zhang, XIN SONG, Yi Xu

NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs

Yao Ni, Piotr Koniusz

Optimal and Fair Encouragement Policy Evaluation and Learning

Angela Zhou

Investigating how ReLU-networks encode symmetries

Georg Bökman, Fredrik Kahl

Model Spider: Learning to Rank Pre-Trained Models Efficiently

Ting-Ji Huang, Yao-Xiang Ding, De-Chuan Zhan, Han-Jia Ye, Yikai Zhang

A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)

Weijie Tu, Weijian Deng, Tom Gedeon

PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation

Zhaoxi Chen, Fangzhou Hong, Haiyi Mei, Guangcong Wang, Lei Yang

Policy Optimization for Continuous Reinforcement Learning

HANYANG ZHAO, Wenpin Tang, David Yao

Balanced Training for Sparse GANs

Yite Wang, Jing Wu, NAIRA HOVAKIMYAN, Ruoyu Sun

Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning

Zih-Yun Chiu, Yi-Lin Tuan, William Yang Wang, Michael Yip

Joint Training of Deep Ensembles Fails Due to Learner Collusion

Alan Jeffares, Tennison Liu, Jonathan Crabbe, Mihaela van der Schaar

Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference

Basile Confavreux, Poornima Ramesh, Pedro J Goncalves, TIm Vogels, Jakob H. Macke

Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests

Edward Raff, James Holt

Understanding Social Reasoning in Language Models with Language Models

Kanishk Gandhi, Jan-Philipp Fraenken, Tobias Gerstenberg, Noah Goodman

Optimization and Bayes: A Trade-off for Overparameterized Neural Networks

Zhengmian Hu, Heng Huang

A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning

Ganyu Wang, Bin Gu, Qingsong Zhang, Xiang Li, Boyu Wang

FaceComposer: A Unified Model for Versatile Facial Content Creation

Jiayu Wang, Kang Zhao, Yifeng Ma, Shiwei Zhang, Yingya Zhang

GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen

Interpretable Graph Networks Formulate Universal Algebra Conjectures

Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Lupidi, Lucie Charlotte Magister

Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback

Shenghuan Sun, Greg Goldgof, Atul Butte, Ahmed M. Alaa

How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget

Guy Hacohen, Daphna Weinshall

Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions

Xiang Cheng, Bohan Wang, Jingzhao Zhang, Yusong Zhu

Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games

Hedi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen

Generalizing Nonlinear ICA Beyond Structural Sparsity

Yujia Zheng, Kun Zhang

WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding

Yanchao Tan, Zihao Zhou, Hang Lv, Weiming Liu, Carl Yang

ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting

Zongsheng Yue, Jianyi Wang, Chen Change Loy

Doubly Constrained Fair Clustering

John Dickerson, Seyed Esmaeili, Jamie H Morgenstern, Claire Jie Zhang

Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery

Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim

PTQD: Accurate Post-Training Quantization for Diffusion Models

Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou

Delegated Classification

Eden Saig, Inbal Talgam-Cohen, Nir Rosenfeld

CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion

Anders Nørskov, Alexander Neergaard Zahid, Morten Mørup

Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language

Kevin Ellis

Thin and deep Gaussian processes

Daniel Augusto de Souza, Alexander Nikitin, ST John, Magnus Ross, Mauricio A Álvarez

Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning

Riccardo Zamboni, Alberto Maria Metelli, Marcello Restelli

On Proper Learnability between Average- and Worst-case Robustness

Vinod Raman, UNIQUE SUBEDI, Ambuj Tewari

Joint Data-Task Generation for Auxiliary Learning

Hong Chen, Xin Wang, Yuwei Zhou, Yijian Qin, Chaoyu Guan

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration

SHUAI ZHANG, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen

A Fractional Graph Laplacian Approach to Oversmoothing

Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok

Uniform Convergence with Square-Root Lipschitz Loss

Lijia Zhou, Zhen Dai, Frederic Koehler, Nati Srebro

On the Importance of Exploration for Generalization in Reinforcement Learning

YiDing Jiang, J. Zico Kolter, Roberta Raileanu

Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints

Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers

A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm

Qi Wang, Yiqin Lv, yanghe feng, Zheng Xie, Jincai Huang

Idempotent Learned Image Compression with Right-Inverse

Yanghao Li, Tongda Xu, Yan Wang, Jingjing Liu, Ya-Qin Zhang

Smooth Flipping Probability for Differential Private Sign Random Projection Methods

Ping Li, Xiaoyun Li

Restless Bandits with Average Reward: Breaking the Uniform Global Attractor Assumption

Yige Hong, Qiaomin Xie, Yudong Chen, Weina Wang

Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage

Masatoshi Uehara, Nathan Kallus, Jason Lee, Wen Sun

Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts

Chaoqi Wang, Ziyu Ye, Zhe Feng, Ashwinkumar Badanidiyuru Varadaraja, Haifeng Xu

Scale-Space Hypernetworks for Efficient Biomedical Image Analysis

Jose Javier Gonzalez Ortiz, John V. Guttag, Adrian Dalca

CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation

Chaoqi Chen, Luyao Tang, Yue Huang, Xiaoguang Han, Yizhou Yu

A Long N-step Surrogate Stage Reward for Deep Reinforcement Learning

Junmin Zhong, Ruofan Wu, Jennie Si

Triangulation Residual Loss for Data-efficient 3D Pose Estimation

Jiachen Zhao, Tao Yu, Liang An, Yipeng Huang, Fang Deng

Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network

Hatef Otroshi Shahreza, Sébastien Marcel

Compositional Sculpting of Iterative Generative Processes

Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski

Weitzman's Rule for Pandora's Box with Correlations

Evangelia Gergatsouli, Christos Tzamos

WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts

Elliott Ash, Naman Goel, Nianyun Li, Claudia Marangon, Peiyao Sun

UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition

Yuyuan Li, Chaochao Chen, Yizhao Zhang, Weiming Liu, Lingjuan Lyu

Composing Parameter-Efficient Modules with Arithmetic Operation

Jinghan Zhang, shiqi chen, Junteng Liu, Junxian He

Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition

Shuhuai Ren, Aston Zhang, Yi Zhu, SHUAI ZHANG, Shuai Zheng

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning

Yihang Yao, ZUXIN LIU, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu

Tanh Works Better with Asymmetry

Dongjin Kim, Woojeong Kim, Suhyun Kim

Adaptive whitening with fast gain modulation and slow synaptic plasticity

Lyndon Duong, Eero P. Simoncelli, Dmitri B. Chklovskii, David Lipshutz

Protein Design with Guided Discrete Diffusion

Nate Gruver, Samuel Stanton, Nathan Frey, Tim G. J. Rudner, Isidro Hotzel

Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning

Changsheng Lv, SHUAI ZHANG, Yapeng Tian, Mengshi Qi, Huadong Ma

Spatio-Angular Convolutions for Super-resolution in Diffusion MRI

Matthew Lyon, Paul Armitage, Mauricio A Álvarez

WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting

Yuxin Jia, Youfang Lin, Xinyan Hao, Yan Lin, Shengnan Guo

Computational Guarantees for Doubly Entropic Wasserstein Barycenters

Tomas Vaskevicius, Lénaïc Chizat

Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision

Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Josh Tenenbaum

Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities

Jingyuan Sun, Mingxiao Li, Zijiao Chen, Yunhao Zhang, Shaonan Wang