NeurIPS 2023

3,540 papers

A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning

Yiyou Sun, Zhenmei Shi, Yixuan Li

ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints

Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions

Michael Scherbela, Leon Gerard, Philipp Grohs

ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding

Lunhao Duan, Shanshan Zhao, Nan Xue, Mingming Gong, Gui-Song Xia

Gradient-Free Kernel Stein Discrepancy

Matthew Fisher, Chris J Oates

InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback

John Yang, Akshara Prabhakar, Karthik Narasimhan, Shunyu Yao

SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks

Bill Yuchen Lin, Yicheng Fu, Karina Yang, Faeze Brahman, Shiyu Huang

Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations

Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour

Separable Physics-Informed Neural Networks

Junwoo Cho, Seungtae Nam, Hyunmo Yang, Seok-Bae Yun, Youngjoon Hong

Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs

Dmitry Chistikov, Matthias Englert, Ranko Lazic

Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent

Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou

$\mathbf{\mathbb{E}^{FWI}}$: Multiparameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

Shihang Feng, Hanchen Wang, Chengyuan Deng, Yinan Feng, Yanhua Liu

A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning

Florian Felten, Lucas N. Alegre, Ann Nowe, Ana Bazzan, El Ghazali Talbi

Regularization properties of adversarially-trained linear regression

Antonio Ribeiro, Dave Zachariah, Francis R. Bach, Thomas Schön

Noise-Adaptive Thompson Sampling for Linear Contextual Bandits

Ruitu Xu, Yifei Min, Tianhao Wang

Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff

Arthur Jacot

Moment Matching Denoising Gibbs Sampling

Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber

Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning

Beichen Zhang, Kun Zhou, Xilin Wei, Xin Zhao, Jing Sha

Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning

Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal

Reusable Slotwise Mechanisms

Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Duy Nguyen, Kartik Ahuja

Continuous Parametric Optical Flow

Jianqin Luo, Zhexiong Wan, yuxin mao, Bo Li, Yuchao Dai

Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting

Hejie Cui, Xinyu Fang, Zihan Zhang, Ran Xu, Xuan Kan

Sample based Explanations via Generalized Representers

Che-Ping Tsai, Chih-Kuan Yeh, Pradeep K Ravikumar, Pradeep K. Ravikumar

CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews

Wojciech Kusa, Oscar E. Mendoza, Matthias Samwald, Petr Knoth, Allan Hanbury

Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes

Zheng Wang, Shikai Fang, Shibo Li, Shandian Zhe

Cascading Contextual Assortment Bandits

Hyun-jun Choi, Rajan Udwani, Min-hwan Oh

Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value

Jaeyeon Kim, Asuman Ozdaglar, Chanwoo Park, Ernest Ryu

Online Nonstochastic Model-Free Reinforcement Learning

Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan

Learning Large Graph Property Prediction via Graph Segment Training

Kaidi Cao, Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou

K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing

Shuai Li, Yingjie Zhang, Hongtu Zhu, Christina Wang, Hai Shu

Understanding Contrastive Learning via Distributionally Robust Optimization

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang

Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks

Alexander Modell, Ian Gallagher, Emma Ceccherini, Nick Whiteley, Patrick Rubin-Delanchy

Prioritizing Samples in Reinforcement Learning with Reducible Loss

Shivakanth Sujit, Somjit Nath, Pedro Braga, Samira Ebrahimi Kahou

Data-Informed Geometric Space Selection

SHUAI ZHANG, Wenqi Jiang

Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars

Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sukthanker, Thomas Brox

A Guide Through the Zoo of Biased SGD

Yury Demidovich, Grigory Malinovsky, Igor Sokolov, Peter Richtarik

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells

Rylan Schaeffer, Mikail Khona, Tzuhsuan Ma, Cristobal Eyzaguirre, Sanmi Koyejo

Diverse Conventions for Human-AI Collaboration

Bidipta Sarkar, Andy Shih, Dorsa Sadigh

Dynamically Masked Discriminator for GANs

Wentian Zhang, Haozhe Liu, Bing Li, Jinheng Xie, Yawen Huang

LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis Evaluation

Yujie Lu, Xianjun Yang, Xiujun Li, Xin Eric Wang, William Yang Wang

Conformal PID Control for Time Series Prediction

Anastasios Angelopoulos, Emmanuel Candes, Ryan J Tibshirani

Explainable and Efficient Randomized Voting Rules

Soroush Ebadian, Aris Filos-Ratsikas, Mohamad Latifian, Nisarg Shah

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency

Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Suggala

Towards Label Position Bias in Graph Neural Networks

Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal

Window-Based Distribution Shift Detection for Deep Neural Networks

Guy Bar-Shalom, Yonatan Geifman, Ran El-Yaniv

SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis

Yuanshao Zhu, Yongchao Ye, Ying Wu, Xiangyu Zhao, James Yu

Near-Optimal k-Clustering in the Sliding Window Model

David Woodruff, Peilin Zhong, Samson Zhou

Thinker: Learning to Plan and Act

Stephen Chung, Ivan Anokhin, David Krueger

Neural Fields with Hard Constraints of Arbitrary Differential Order

Fangcheng Zhong, Kyle Fogarty, Param Hanji, Tianhao Wu, Alejandro Sztrajman

Iteratively Learn Diverse Strategies with State Distance Information

Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang

Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering

Weizhe Lin, Jinghong Chen, Jingbiao Mei, Alexandru Coca, Bill Byrne

D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts

Fenggen Yu, Qimin Chen, Maham Tanveer, Ali Mahdavi Amiri, Hao Zhang

Grounding Neural Inference with Satisfiability Modulo Theories

Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha

Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization

Wenzhi Gao, Qi Deng

Attacks on Online Learners: a Teacher-Student Analysis

Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti

Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation

Jianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu

Hybrid Search for Efficient Planning with Completeness Guarantees

Kalle Kujanpää, Joni K. Pajarinen, Alexander Ilin

SPRING: Studying Papers and Reasoning to play Games

Yue Wu, So Yeon Min, Shrimai Prabhumoye, Yonatan Bisk, Ruslan Salakhutdinov

Convergence of Alternating Gradient Descent for Matrix Factorization

Rachel Ward, Tamara Kolda

UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation

Muchao Ye, Ziyi Yin, Tianrong Zhang, Tianyu Du, Jinghui Chen

Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

Xin Yan, Hui Fang, Qiang He

Compositional Foundation Models for Hierarchical Planning

Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta

Generalized test utilities for long-tail performance in extreme multi-label classification

Erik Schultheis, Marek Wydmuch, Wojciech Kotlowski, Rohit Babbar, Krzysztof J. Dembczynski

VeriX: Towards Verified Explainability of Deep Neural Networks

Min Wu, Haoze Wu, Clark Barrett

One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization

Minghua Liu, Chao Xu, Haian Jin, Linghao Chen, Mukund Varma T

Learning and Collusion in Multi-unit Auctions

Simina Branzei, Mahsa Derakhshan, Negin Golrezaei, Yanjun Han

Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks

Yun Qu, Boyuan Wang, Jianzhun Shao, Yuhang Jiang, Chen Chen

Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration

Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu

Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping

Tianhao Wu, Mingdong Wu, Jiyao Zhang, Yunchong Gan, Hao Dong

Boosting Learning for LDPC Codes to Improve the Error-Floor Performance

Hee-Youl Kwak, Dae-Young Yun, Yongjune Kim, Sang-Hyo Kim, Jong-Seon No

Connecting Multi-modal Contrastive Representations

Zehan Wang, Yang Zhao, Xize 成, Haifeng Huang, Jiageng Liu

Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification

Liangliang Shi, Haoyu Zhen, Gu Zhang, Junchi Yan

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Sungduk Yu, Walter Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri

Improving multimodal datasets with image captioning

Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt

Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning

Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris Papailiopoulos, Samet Oymak

Learning the Efficient Frontier

Philippe Chatigny, Ivan Sergienko, Ryan Ferguson, Jordan Weir, Maxime Bergeron

Evolving Standardization for Continual Domain Generalization over Temporal Drift

Mixue Xie, Shuang Li, Longhui Yuan, Chi Liu, Zehui Dai

Can semi-supervised learning use all the data effectively? A lower bound perspective

Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang

Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system

Suhas Shrinivasan, Konstantin-Klemens Lurz, Kelli Restivo, George Denfield, Andreas Tolias

On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails

Yi Feng, Hu Fu, Qun Hu, Ping Li, Ioannis Panageas

Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection

Yuxin Cao, Yian Li, Yumeng Zhu, Derui Wang, Minhui Xue

Optimal Rates for Bandit Nonstochastic Control

Y. Jennifer Sun, Stephen Newman, Elad Hazan

Scaling laws for language encoding models in fMRI

Richard Antonello, Aditya Vaidya, Alexander Huth

PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation

Jialu Li, Mohit Bansal

No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling

Eric Neyman, Tim Roughgarden

Data-Driven Network Neuroscience: On Data Collection and Benchmark

Jiaxing Xu, Yunhan Yang, David Huang, Sophi Shilpa Gururajapathy, Yiping Ke

Explain Any Concept: Segment Anything Meets Concept-Based Explanation

Ao Sun, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang

Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise

Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis

ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning

Julia Kaltenborn, Charlotte Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz

Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives

Yahong Yang, Haizhao Yang, Yang Xiang

LLM-Pruner: On the Structural Pruning of Large Language Models

Xinyin Ma, Gongfan Fang, Xinchao Wang

RegBN: Batch Normalization of Multimodal Data with Regularization

Morteza Ghahremani Boozandani, Christian Wachinger

A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings

Nathaniel Lahn, Sharath Raghvendra, Kaiyi Zhang

Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models

Aaron Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Bin Hu

Neuro-symbolic Learning Yielding Logical Constraints

Zenan Li, Yunpeng Huang, Zhaoyu Li, Yuan Yao, Jingwei Xu

Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections

Talia Konkle, George Alvarez

LeanDojo: Theorem Proving with Retrieval-Augmented Language Models

Kaiyu Yang, Aidan Swope, Alex Gu, Rahul Chalamala, Peiyang Song

Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation

Chunqiu Steven Xia, Yuyao Wang, LINGMING ZHANG, Jia-Wei Liu, Jiawei Liu

Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun

Does Visual Pretraining Help End-to-End Reasoning?

Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid