NeurIPS 2023

3,540 papers

All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation

Liyao Tang, Zhe Chen, Shanshan Zhao, Chaoyue Wang, Dacheng Tao

PreDiff: Precipitation Nowcasting with Latent Diffusion Models

Zhihan Gao, Xingjian SHI, Boran Han, Hao Wang, Xiaoyong Jin

Block Coordinate Plug-and-Play Methods for Blind Inverse Problems

Weijie Gan, shirin shoushtari, Yuyang Hu, Jiaming Liu, Hongyu An

Neural Sampling in Hierarchical Exponential-family Energy-based Models

Xingsi Dong, Si Wu

L_2-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting

Xiaotong Yuan, Ping Li

HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection

Xingbo Du, Chonghua Wang, Ruizhe Zhong, Junchi Yan

The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games

Victor Boone, Panayotis Mertikopoulos

Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning

Zikang Tian, Ruizhi Chen, Xing Hu, Ling Li, Rui Zhang

CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss

Rakshith Sharma Srinivasa, Jaejin Cho, Chouchang Yang, Yashas Malur Saidutta, Ching-Hua Lee

M5HisDoc: A Large-scale Multi-style Chinese Historical Document Analysis Benchmark

Yongxin Shi, Chongyu Liu, Dezhi Peng, Cheng Jian, Jiarong Huang

Accelerating Motion Planning via Optimal Transport

An T. Le, Georgia Chalvatzaki, Armin Biess, Jan R. Peters, Jan R Peters

Learning Invariant Molecular Representation in Latent Discrete Space

Xiang Zhuang, Qiang Zhang, Keyan Ding, Yatao Bian, Xiao Wang

Contextual Stochastic Bilevel Optimization

Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Huhn

Collapsed Inference for Bayesian Deep Learning

Zhe Zeng, Guy Van den Broeck

MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks

Allen Nie, Yuhui Zhang, Atharva Shailesh Amdekar, Chris Piech, Tatsunori B Hashimoto

Kiki or Bouba? Sound Symbolism in Vision-and-Language Models

Morris Alper, Hadar Averbuch-Elor

Boundary Guided Learning-Free Semantic Control with Diffusion Models

Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, Yan Yan

Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs

Kevin Course, Prasanth Nair

OceanBench: The Sea Surface Height Edition

J. Emmanuel Johnson, Quentin Febvre, Anastasiia Gorbunova, Sam Metref, Maxime Ballarotta

Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision

Jiaxin Zhang, Zhuohang Li, Kamalika Das, Sricharan Kumar

BIOT: Biosignal Transformer for Cross-data Learning in the Wild

Chaoqi Yang, M Westover, Jimeng Sun

Large Language Models Are Semi-Parametric Reinforcement Learning Agents

Danyang Zhang, Lu Chen, Situo Zhang, Hongshen Xu, Zihan Zhao

Interpretability at Scale: Identifying Causal Mechanisms in Alpaca

Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah Goodman

False Discovery Proportion control for aggregated Knockoffs

Alexandre Blain, Bertrand Thirion, Olivier Grisel, Pierre Neuvial

Monte Carlo Tree Search with Boltzmann Exploration

Michael Painter, Mohamed Baioumy, Nick Hawes, Bruno Lacerda

Granger Components Analysis: Unsupervised learning of latent temporal dependencies

Jacek Dmochowski

Benchmarking Foundation Models with Language-Model-as-an-Examiner

Yushi Bai, Jiahao Ying, Yixin Cao, Xin Lv, Yuze He

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology

Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization

Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar

Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection

Lingchen Meng, Xiyang Dai, Jianwei Yang, Dongdong Chen, Yinpeng Chen

A Dataset for Analyzing Streaming Media Performance over HTTP/3 Browsers

Sapna Chaudhary, Mukulika Maity, Sandip Chakraborty, Naval Shukla

Should Under-parameterized Student Networks Copy or Average Teacher Weights?

Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea

Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets

Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill

PrObeD: Proactive Object Detection Wrapper

Vishal Asnani, Abhinav Kumar, Suya You, Xiaoming Liu

Learning from Active Human Involvement through Proxy Value Propagation

Zhenghao (Mark) Peng, Wenjie Mo, Chenda Duan, Quanyi Li, Bolei Zhou

Text Alignment Is An Efficient Unified Model for Massive NLP Tasks

Yuheng Zha, Yichi Yang, Ruichen Li, Zhiting Hu

Context-lumpable stochastic bandits

Chung-Wei Lee, Qinghua Liu, Yasin Abbasi Yadkori, Chi Jin, Tor Lattimore

Adaptive Test-Time Personalization for Federated Learning

Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He

Metis: Understanding and Enhancing In-Network Regular Expressions

Zhengxin Zhang, Yucheng Huang, Guanglin Duan, Qing Li, Dan Zhao

Anytime-Competitive Reinforcement Learning with Policy Prior

Jianyi Yang, Pengfei Li, Tongxin Li, Adam Wierman, Shaolei Ren

MedSat: A Public Health Dataset for England Featuring Medical Prescriptions and Satellite Imagery

Sanja Scepanovic, Ivica Obadic, Sagar Joglekar, Laura GIUSTARINI, Cristiano Nattero

On Differentially Private Sampling from Gaussian and Product Distributions

Badih Ghazi, Xiao Hu, Ravi Kumar, Pasin Manurangsi

GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image

Mingjian Zhu, Hanting Chen, Qiangyu YAN, Xudong Huang, Guanyu Lin

CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data

Taiki Miyanishi, Fumiya Kitamori, Shuhei Kurita, Jungdae Lee, Motoaki Kawanabe

Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer

Zikai Xiao, Zihan Chen, Songshang Liu, Hualiang Wang, Yang Feng

How to Turn Your Knowledge Graph Embeddings into Generative Models

Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari

Unbounded Differentially Private Quantile and Maximum Estimation

David Durfee

Social Motion Prediction with Cognitive Hierarchies

Wentao Zhu, Jason Qin, Yuke Lou, Hang Ye, Xiaoxuan Ma

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models

Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun

Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Yizi Zhang, Tianxiao He, Julien Boussard, Charles Windolf, Olivier Winter

Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture

Dan Fu, Simran Arora, Jessica Grogan, Isys Johnson, Evan Sabri Eyuboglu

One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning

Marc Rigter, Bruno Lacerda, Nick Hawes

LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion

Jiaqi Guan, Xingang Peng, PeiQi Jiang, Yunan Luo, Jian Peng

Neural Functional Transformers

Allan Zhou, Kaien Yang, YiDing Jiang, Kaylee Burns, Winnie Xu

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data

Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung

BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization

Darko Drakulic, Sofia Michel, Florian Mai, Arnaud Sors, Jean-Marc Andreoli

PoET: A generative model of protein families as sequences-of-sequences

Timothy Truong Jr, Tristan Bepler

M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery

Yuanqi Du, Yingheng Wang, Yining Huang, Jianan Canal Li, Yanqiao Zhu

Mnemosyne: Learning to Train Transformers with Transformers

Deepali Jain, Krzysztof M Choromanski, Kumar Avinava Dubey, Sumeet Singh, Vikas Sindhwani

Black-Box Differential Privacy for Interactive ML

Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer

Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning

Jianzhun Shao, Yun Qu, Chen Chen, Hongchang Zhang, Xiangyang Ji

Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors

Chengxu Zuo, Fang Jiawei, Shihui Guo, Yipeng Qin

Estimating Koopman operators with sketching to provably learn large scale dynamical systems

Giacomo Meanti, Antoine Chatalic, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil

Neural Image Compression: Generalization, Robustness, and Spectral Biases

Kelsey Lieberman, James Diffenderfer, Charles Godfrey, Bhavya Kailkhura

Convolutional Neural Operators for robust and accurate learning of PDEs

Bogdan Raonic, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci

L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors

Zheng Chang, Shuchen Weng, Peixuan Zhang, Yu Li, Si Li

The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium

Shuyue Hu, Harold Soh, Georgios Piliouras

VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception

Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi

Adaptive Principal Component Regression with Applications to Panel Data

Anish Agarwal, Keegan Harris, Justin Whitehouse, Steven Z. Wu

One-step differentiation of iterative algorithms

Jérôme Bolte, Edouard Pauwels, Samuel Vaiter

Function Space Bayesian Pseudocoreset for Bayesian Neural Networks

Balhae Kim, Hyungi Lee, Juho Lee

Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning

Stefan Stojanovic, Yassir Jedra, Alexandre Proutiere

Efficiently incorporating quintuple interactions into geometric deep learning force fields

Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao

Evaluating Open-QA Evaluation

Cunxiang Wang, Sirui Cheng, Qipeng Guo, Yuanhao Yue, Bowen Ding

Doubly Robust Augmented Transfer for Meta-Reinforcement Learning

Yuankun Jiang, Nuowen Kan, Chenglin Li, Wenrui Dai, Junni Zou

Differentially Private Statistical Inference through β-Divergence One Posterior Sampling

Jack E Jewson, Sahra Ghalebikesabi, Chris C Holmes

InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion

Fangzhou Lin, Yun Yue, Ziming Zhang, Songlin Hou, Kazunori Yamada

Exponentially Convergent Algorithms for Supervised Matrix Factorization

Joowon Lee, Hanbaek Lyu, Weixin Yao

GAUCHE: A Library for Gaussian Processes in Chemistry

Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang Truong

Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification

Rui Wang, Peipei Li, Huaibo Huang, Chunshui Cao, Ran He

ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition

Aashaka Desai, Lauren Berger, Fyodor Minakov, Nessa Milano, Chinmay Singh

Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation

Quang Nguyen, Truong Vu, Anh Tran, Khoi Nguyen

Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models

Haonan Duan, Adam Dziedzic, Nicolas Papernot, Franziska Boenisch

Constructing Non-isotropic Gaussian Diffusion Model Using Isotropic Gaussian Diffusion Model for Image Editing

Xi Yu, Xiang Gu, Haozhi Liu, Jian Sun

Restart Sampling for Improving Generative Processes

Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu

The Tunnel Effect: Building Data Representations in Deep Neural Networks

Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Miłoś

Self-Chained Image-Language Model for Video Localization and Question Answering

Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal

Interpretable Prototype-based Graph Information Bottleneck

Sangwoo Seo, Sungwon Kim, Chanyoung Park

Alternating Updates for Efficient Transformers

Cenk Baykal, Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy

Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence

Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada

Q-DM: An Efficient Low-bit Quantized Diffusion Model

Yanjing Li, Sheng Xu, Xianbin Cao, Xiao Sun, Baochang Zhang

Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang

Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction

Chih-Yu (Andrew) Lai, Fan-Keng Sun, Zhengqi Gao, Jeffrey H Lang, Duane Boning

Parallel-mentoring for Offline Model-based Optimization

Can (Sam) Chen, Christopher Beckham, Zixuan Liu, Xue (Steve) Liu, Chris Pal

Expanding Small-Scale Datasets with Guided Imagination

Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng

Characterization of Overfitting in Robust Multiclass Classification

Jingyuan Xu, Weiwei Liu

Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models

Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li

Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes

Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini

Momentum Provably Improves Error Feedback!

Ilyas Fatkhullin, Alexander Tyurin, Peter Richtarik

Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer

Suren Jayasuriya, Visar Berisha, Jian-Wei Zhang, Jianwei Zhang