NeurIPS 2023

3,540 papers

ANPL: Towards Natural Programming with Interactive Decomposition

Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin, shaohui peng

xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data

Jing Gong, Minsheng Hao, Xingyi Cheng, Xin Zeng, Chiming Liu

Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability

Jishnu Ray Chowdhury, Cornelia Caragea

Recurrent Temporal Revision Graph Networks

Yizhou Chen, Qingtao Yu, Kerui Zhang, Cao Yuanpeng, Kangle Wu

MG-ViT: A Multi-Granularity Method for Compact and Efficient Vision Transformers

Yu Zhang, Yepeng Liu, Duoqian Miao, Qi Zhang, Yiwei Shi

StableFDG: Style and Attention Based Learning for Federated Domain Generalization

Jungwuk Park, Dong-Jun Han, Jinho Kim, Shiqiang Wang, Christopher Brinton

On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis

Ta Duy Nguyen, Alina Ene, Huy Nguyen

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations

Anudhyan Boral, Zhong Yi Wan, Leonardo Zepeda-Núñez, James Lottes, Qing Wang

Robust Bayesian Satisficing

Artun Saday, Y. Cahit Yıldırım, Cem Tekin

Normalization Layers Are All That Sharpness-Aware Minimization Needs

Maximilian Mueller, Tiffany Vlaar, David Rolnick, Matthias Hein

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

Wei-Ning Chen, Dan Song, Ayfer Ozgur, Peter Kairouz

Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability

Jonathan Zedaka, Elisha Halperin, Evgeny Blaichman, Amit Berman

Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval

Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg

Information-guided Planning: An Online Approach for Partially Observable Problems

Matheus Aparecido Do Carmo Alves, Amokh Varma, Yehia Elkhatib, Leandro Soriano Marcolino

DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng

Inverse Reinforcement Learning with the Average Reward Criterion

Feiyang Wu, Jingyang Ke, Anqi Wu

Accessing Higher Dimensions for Unsupervised Word Translation

Sida Wang

3D molecule generation by denoising voxel grids

Pedro O O. Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, Omar Mahmood

Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality

Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su

On permutation symmetries in Bayesian neural network posteriors: a variational perspective

Simone Rossi, Ankit Singh, Thomas Hannagan

Statistical and Computational Trade-off in Multi-Agent Multi-Armed Bandits

Filippo Vannella, Alexandre Proutiere, Jaeseong Jeong

Non-Asymptotic Analysis of a UCB-based Top Two Algorithm

Marc Jourdan, Rémy Degenne

Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee

Yuanshi Liu, Cong Fang, Tong Zhang

Utilitarian Algorithm Configuration

Devon Graham, Kevin Leyton-brown, Tim Roughgarden

On the Adversarial Robustness of Out-of-distribution Generalization Models

Xin Zou, Weiwei Liu

Label-Only Model Inversion Attacks via Knowledge Transfer

Bao-Ngoc Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man (Man) Cheung

Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion

Ethan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy, Zeyu Wang, Andres Morales

Human-Guided Complexity-Controlled Abstractions

Andi Peng, Mycal Tucker, Eoin Kenny, Noga Zaslavsky, Pulkit Agrawal

Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders

Lai Wei, Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu

Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation

Yun Xing, Jian Kang, Aoran Xiao, Jiahao Nie, Ling Shao

Provably (More) Sample-Efficient Offline RL with Options

Xiaoyan Hu, Ho-fung Leung

Video Prediction Models as Rewards for Reinforcement Learning

Alejandro Escontrela, Ademi Adeniji, Wilson Yan, Ajay N. Jain, Xue Bin Peng

Tight Risk Bounds for Gradient Descent on Separable Data

Matan Schliserman, Tomer Koren

HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count

Noah Wiederhold, Ava Megyeri, DiMaggio Paris, Sean Banerjee, Natasha Banerjee

Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis

Alexander Meulemans, Simon Schug, Seijin Kobayashi, nathaniel daw, Gregory Wayne

A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems

Matthew Bendel, Rizwan Ahmad, Philip Schniter

Emergent Communication for Rules Reasoning

Yuxuan Guo, Yifan Hao, Rui Zhang, Enshuai Zhou, Zidong Du

Parallel Submodular Function Minimization

Deeparnab Chakrabarty, Andrei Graur, Haotian Jiang, Aaron Sidford

ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks

Jongseok Park, Kyungmin Bin, Gibum Park, Sangtae Ha, Kyunghan Lee

Individual Arbitrariness and Group Fairness

Carol Long, Hsiang Hsu, Wael Alghamdi, Flavio Calmon

Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models

Naoki Egami, Musashi Hinck, Brandon Stewart, Hanying Wei

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case

Taihei Oki, Shinsaku Sakaue

The probability flow ODE is provably fast

Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu

Toolformer: Language Models Can Teach Themselves to Use Tools

Timo Schick, Jane Dwivedi-Yu, Roberto Dessi, Roberta Raileanu, Maria Lomeli

Proximity-Informed Calibration for Deep Neural Networks

Miao Xiong, Ailin Deng, Pang Wei W Koh, Jiaying Wu, Shen Li

rPPG-Toolbox: Deep Remote PPG Toolbox

Xin Liu, Girish Narayanswamy, Akshay Paruchuri, Xiaoyu Zhang, Jiankai Tang

Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork

Qiang Gao, Xiaojun Shan, Yuchen Zhang, Fan Zhou

DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation

Jiuhn Song, Seonghoon Park, Honggyu An, Seokju Cho, Min-Seop Kwak

Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees

Wenqi Cui, Yan Jiang, Baosen Zhang, Yuanyuan Shi

Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method

Tianyi Liu, Kejun Wu, Yi Wang, Wenyang Liu, Kim-Hui Yap

Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms

Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao

OpenMask3D: Open-Vocabulary 3D Instance Segmentation

Ayca Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari

Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping

Yingbin Bai, Zhongyi Han, Erkun Yang, Jun Yu, Bo Han

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures

David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve OUDOT

Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning

Chang Lu, Chandan Reddy, Ping Wang, Yue Ning

Train Hard, Fight Easy: Robust Meta Reinforcement Learning

Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom

Understanding and Improving Feature Learning for Out-of-Distribution Generalization

Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han

ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

Zhangyang Gao, Cheng Tan, Yijie Zhang, Xingran Chen, Lirong Wu

Nearly Optimal Bounds for Cyclic Forgetting

William Swartworth, Deanna Needell, Rachel Ward, Mark Kong, Halyun Jeong

UP-NeRF: Unconstrained Pose Prior-Free Neural Radiance Field

Injae Kim, Minhyuk Choi, Hyunwoo J Kim

Private estimation algorithms for stochastic block models and mixture models

Hongjie Chen, Vincent Cohen-Addad, Tommaso d’Orsi, Alessandro Epasto, Jacob Imola

Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms

Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen

SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models

Martin Gonzalez, Nelson Fernandez Pinto, Thuy Tran, elies Gherbi, Hatem Hajri

Evaluating Self-Supervised Learning for Molecular Graph Embeddings

Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Joan Lasenby

Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability

David Liu, Máté Lengyel

Dynamic Sparsity Is Channel-Level Sparsity Learner

Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries

Joshua Engels, Benjamin Coleman, Vihan Lakshman, Anshumali Shrivastava

DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation

Shentong Mo, Enze Xie, Ruihang Chu, Lanqing Hong, Matthias Niessner

Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions

Chengzhi Cao, Chao Yang, Ruimao Zhang, Shuang Li

A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process

Jiayu Chen, Vaneet Aggarwal, Tian Lan

Reliable Off-Policy Learning for Dosage Combinations

Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Hardware Resilience Properties of Text-Guided Image Classifiers

Syed Talal Wasim, Kabila Haile Soboka, Abdulrahman Mahmoud, Salman H Khan, David Brooks

Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization

Runqi Lin, Chaojian Yu, Tongliang Liu

Affinity-Aware Graph Networks

Ameya Velingker, Ali Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi

Video-Mined Task Graphs for Keystep Recognition in Instructional Videos

Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman

COOM: A Game Benchmark for Continual Reinforcement Learning

Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy

Policy Space Diversity for Non-Transitive Games

Jian Yao, Weiming Liu, Haobo Fu, Yaodong Yang, Stephen Mcaleer

The Crucial Role of Normalization in Sharpness-Aware Minimization

Yan Dai, Kwangjun Ahn, Suvrit Sra

UDC-SIT: A Real-World Dataset for Under-Display Cameras

Kyusu Ahn, Byeonghyun Ko, HyunGyu Lee, Chanwoo Park, Jaejin Lee

Implicit Manifold Gaussian Process Regression

Bernardo Fichera, Slava Borovitskiy, Andreas Krause, Aude G Billard

Towards Better Dynamic Graph Learning: New Architecture and Unified Library

Le Yu, Leilei Sun, Bowen Du, Weifeng Lv

Statistically Valid Variable Importance Assessment through Conditional Permutations

Ahmad CHAMMA, Denis A. Engemann, Bertrand Thirion

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences

Minsu Kim, Federico Berto, Sungsoo Ahn, Jinkyoo Park

An Efficient Dataset Condensation Plugin and Its Application to Continual Learning

Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo

Fast Approximation of Similarity Graphs with Kernel Density Estimation

Peter Macgregor, He Sun

Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends

Wang Xinrui, Wenhai Wan, Chuanxing Geng, Shao-Yuan Li, Songcan Chen

State Sequences Prediction via Fourier Transform for Representation Learning

Mingxuan Ye, Yufei Kuang, Jie Wang, Yang Rui, Wengang Zhou

The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification

Linhao Qu, xiaoyuan luo, Kexue Fu, Manning Wang, Zhijian Song

Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective

Yifei Zhang, Hao Zhu, yankai Chen, Zixing Song, Piotr Koniusz

SLaM: Student-Label Mixing for Distillation with Unlabeled Examples

Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani

Sequential Subset Matching for Dataset Distillation

JIAWEI DU, Qin Shi, Joey Tianyi Zhou

An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, Max Springer

Towards a Unified Framework of Contrastive Learning for Disentangled Representations

Stefan Matthes, Zhiwei Han, Hao Shen

Accelerating Exploration with Unlabeled Prior Data

Qiyang Li, Jason Zhang, Dibya Ghosh, Amy Zhang, Sergey Levine

PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers

Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard Turner, Johannes Brandstetter

Multi-scale Diffusion Denoised Smoothing

Jongheon Jeong, Jinwoo Shin

SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning

Yunxiang Zhang, Xiaojun Wan

DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model

Xiuye Gu, Yin Cui, Jonathan Huang, Abdullah Rashwan, Xuan Yang

From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Models to Pre-trained Machine Reader

Weiwen Xu, Xin Li, Wenxuan Zhang, Meng Zhou, Wai Lam

Learning Regularized Monotone Graphon Mean-Field Games

Fengzhuo Zhang, Vincent Tan, Zhaoran Wang, Zhuoran Yang