NeurIPS 2023

3,540 papers

Lovász Principle for Unsupervised Graph Representation Learning

Ziheng Sun, Chris Ding, Jicong Fan

ProteinShake: Building datasets and benchmarks for deep learning on protein structures

Tim Kucera, Carlos Oliver, Dexiong Chen, Karsten Borgwardt

Fairness Aware Counterfactuals for Subgroups

Loukas Kavouras, Konstantinos Tsopelas, Giorgos Giannopoulos, Dimitris Sacharidis, Eleni Psaroudaki

AdaPlanner: Adaptive Planning from Feedback with Language Models

Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, Chao Zhang

Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network

Bochen Lyu, Zhanxing Zhu

On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

Yufeng Zhang, Jialu Pan, Li Ken Li, Wanwei Liu, Zhenbang Chen

Joint Prompt Optimization of Stacked LLMs using Variational Inference

Alessandro Sordoni, Eric Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler

A Massive Scale Semantic Similarity Dataset of Historical English

Emily Silcock, Abhishek Arora, Melissa Dell

Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions

Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner

Understanding and Improving Ensemble Adversarial Defense

Yian Deng, Tingting Mu

MVDoppler: Unleashing the Power of Multi-View Doppler for MicroMotion-based Gait Classification

Soheil Hor, Shubo Yang, Jaeho Choi, Amin Arbabian

Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images

Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein

From Tempered to Benign Overfitting in ReLU Neural Networks

Guy Kornowski, Gilad Yehudai, Ohad Shamir

Switching Autoregressive Low-rank Tensor Models

Hyun Dong Lee, Andrew Warrington, Joshua Glaser, Scott Linderman

Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy

Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park

MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection

Junho Song, Keonwoo Kim, Jeonglyul Oh, Sungzoon Cho

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

Mirac Suzgun, Luke Melas-Kyriazi, Suproteem Sarkar, Scott D Kominers, Stuart Shieber

Scale Alone Does not Improve Mechanistic Interpretability in Vision Models

Roland S. Zimmermann, Thomas Klein, Wieland Brendel

Norm-guided latent space exploration for text-to-image generation

Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik

Optimistic Meta-Gradients

Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado P van Hasselt, András György

Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation

Seunghwan An, Jong-June Jeon

Penalising the biases in norm regularisation enforces sparsity

Etienne Boursier, Nicolas Flammarion

PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis

Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen, Nesreen K. Ahmed, Ali Jannesari

On the Convergence of CART under Sufficient Impurity Decrease Condition

Rahul Mazumder, Haoyue Wang

Globally injective and bijective neural operators

Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop

Residual Alignment: Uncovering the Mechanisms of Residual Networks

Jianing Li, Vardan Papyan

General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence

Lingwei Zhu, Zheng Chen, Matthew Schlegel, Martha White

Adversarial Learning for Feature Shift Detection and Correction

Míriam Barrabés, Daniel Mas Montserrat, Margarita Geleta, Xavier Giró-i-Nieto, Alexander Ioannidis

Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations

Arun Jambulapati, Kevin Tian

Masked Image Residual Learning for Scaling Deeper Vision Transformers

Guoxi Huang, Hongtao Fu, Adrian G. Bors

Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping

Feng Zhang, Ming Tian, Zhiqiang Li, Bin Xu, Qingbo Lu

How do Minimum-Norm Shallow Denoisers Look in Function Space?

Chen Zeno, Greg Ongie, Yaniv Blumenfeld, Nir Weinberger, Daniel Soudry

Customizable Image Synthesis with Multiple Subjects

Zhiheng Liu, Yifei Zhang, Yujun Shen, Kecheng Zheng, Kai Zhu

Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding

Zhejun Zhang, Alexander Liniger, Christos Sakaridis, Fisher Yu, Luc V Gool

Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time

Arvind Mahankali, Haochen Zhang, Kefan Dong, Margalit Glasgow, Tengyu Ma

Black-box Backdoor Defense via Zero-shot Image Purification

Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun

On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes

Rajat Modi, Vibhav Vineet, Yogesh Rawat

Learning Provably Robust Estimators for Inverse Problems via Jittering

Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel

IDEA: An Invariant Perspective for Efficient Domain Adaptive Image Retrieval

Haixin Wang, Hao Wu, Jinan Sun, Shikun Zhang, Chong Chen

A Theory of Multimodal Learning

Zhou Lu

FAMO: Fast Adaptive Multitask Optimization

Bo Liu, Yihao Feng, Peter Stone, Qiang Liu

Arbitrarily Scalable Environment Generators via Neural Cellular Automata

Yulun Zhang, Matthew Fontaine, Varun Bhatt, Stefanos Nikolaidis, Jiaoyang Li

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection

Yu Bai, Fan Chen, Huan Wang, Caiming Xiong, Song Mei

Domain Re-Modulation for Few-Shot Generative Domain Adaptation

Yi Wu, Ziqiang Li, Chaoyue Wang, Heliang Zheng, Shanshan Zhao

Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation

Weihang Dai, Yao DU, Hanru Bai, Kwang-Ting Cheng, Xiaomeng Li

Deep Momentum Multi-Marginal Schrödinger Bridge

Tianrong Chen, Guan-Horng Liu, Molei Tao, Evangelos Theodorou

Self-Consistent Velocity Matching of Probability Flows

Lingxiao Li, Samuel Hurault, Justin M Solomon

The emergence of clusters in self-attention dynamics

Borjan Geshkovski, Cyril Letrouit, Yury Polyanskiy, Philippe Rigollet

Latent Diffusion for Language Generation

Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, Kilian Q. Weinberger

Brain-like Flexible Visual Inference by Harnessing Feedback Feedforward Alignment

Tahereh Toosi, Elias Issa

Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks

Jiarong Xu, Renhong Huang, Xin Jiang, Yuxuan Cao, Carl Yang

GenS: Generalizable Neural Surface Reconstruction from Multi-View Images

Rui Peng, Xiaodong Gu, Luyang Tang, Shihe Shen, Fanqi Yu

Multi-Head Adapter Routing for Cross-Task Generalization

Lucas Page-Caccia, Edoardo Maria Ponti, Zhan Su, Matheus Pereira, Nicolas Le Roux

Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory

Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain

Effective Targeted Attacks for Adversarial Self-Supervised Learning

Minseon Kim, Hyeonjeong Ha, Sooel Son, Sung Ju Hwang

DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field

Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt

Streaming Factor Trajectory Learning for Temporal Tensor Decomposition

Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby

QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution

Haotong Qin, Yulun Zhang, Yifu Ding, Yifan liu, Xianglong Liu

Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

Jinbiao Chen, Jiahai Wang, Zizhen Zhang, Zhiguang Cao, Te Ye

Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion

Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, Jungwoo Lee

Add and Thin: Diffusion for Temporal Point Processes

David Lüdke, Marin Biloš, Oleksandr Shchur, Marten Lienen, Stephan Günnemann

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination

Osama Hanna, Lin Yang, Christina Fragouli

Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning

Wei Tang, Weijia Zhang, Min-ling Zhang

Convergence Analysis of Sequential Federated Learning on Heterogeneous Data

Yipeng Li, Xinchen Lyu

Exploring and Interacting with the Set of Good Sparse Generalized Additive Models

Chudi Zhong, Zhi Chen, Jiachang Liu, Margo Seltzer, Cynthia Rudin

On-the-Fly Adapting Code Summarization on Trainable Cost-Effective Language Models

Yufan Cai, Yun Lin, Chenyan Liu, Jinglian Wu, Yifan Zhang

R-divergence for Estimating Model-oriented Distribution Discrepancy

Zhilin Zhao, Longbing Cao

Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms

Michael Feldman, David Donoho

Exploring Question Decomposition for Zero-Shot VQA

Zaid Khan, Vijay Kumar B G, Samuel Schulter, Manmohan Chandraker, Yun Fu

A Bayesian Take on Gaussian Process Networks

Enrico Giudice, Jack Kuipers, Giusi Moffa

Learning Dictionary for Visual Attention

Yingjie Liu, Xuan Liu, Hui Yu, XUAN TANG, xian wei

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds

Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang

Group Robust Classification Without Any Group Information

Christos Tsirigotis, Joao Monteiro, Pau Rodriguez, David Vázquez, Aaron C. Courville

Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning

Tyler Kastner, Murat A Erdogdu, Amir-massoud Farahmand

Latent exploration for Reinforcement Learning

Alberto Silvio Chiappa, Alessandro Marin Vargas, Ann Huang, Alexander Mathis

Beyond Average Return in Markov Decision Processes

Alexandre Marthe, Aurélien Garivier, Claire Vernade

V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs

Senzhang Wang, Jun Yin, Chaozhuo Li, Xing Xie, Jianxin Wang

New Complexity-Theoretic Frontiers of Tractability for Neural Network Training

Cornelius Brand, Robert Ganian, Mathis Rocton

MGDD: A Meta Generator for Fast Dataset Distillation

Songhua Liu, Xinchao Wang

Self-Supervised Reinforcement Learning that Transfers using Random Features

Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta

L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference

Julia Linhart, Alexandre Gramfort, Pedro Rodrigues

Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search

Indradyumna Roy, Rishi Agarwal, Soumen Chakrabarti, Anirban Dasgupta, Abir De

Stable Bias: Evaluating Societal Representations in Diffusion Models

Sasha Luccioni, Christopher Akiki, Margaret Mitchell, Yacine Jernite

Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective

João Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, Joachim M Buhmann

The CLIP Model is Secretly an Image-to-Prompt Converter

Yuxuan Ding, Chunna Tian, Haoxuan Ding, Lingqiao Liu

A Batch-to-Online Transformation under Random-Order Model

Jing Dong, Yuichi Yoshida

Counterfactual Generation with Identifiability Guarantees

Hanqi Yan, Lingjing Kong, Lin Gui, Yuejie Chi, Eric P. Xing

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong

Individualized Dosing Dynamics via Neural Eigen Decomposition

Stav Belogolovsky, Ido Greenberg, Danny Eytan, Shie Mannor

Coordinating Distributed Example Orders for Provably Accelerated Training

A. Feder Cooper, Wentao Guo, Duc Khiem Pham, Tiancheng Yuan, Charlie Ruan

Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias

Zhongwei Wan, Che Liu, Mi Zhang, Jie Fu, Benyou Wang

A Scalable Neural Network for DSIC Affine Maximizer Auction Design

Zhijian Duan, Haoran Sun, Yurong Chen, Xiaotie Deng

Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity

Metod Jazbec, James Allingham, Dan Zhang, Eric Nalisnick

Learning via Wasserstein-Based High Probability Generalisation Bounds

Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj

Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks

Alex Schlögl, Nora Hofer, Rainer Böhme

Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks

Haoyi Duan, Yan Xia, Zhou Mingze, Li Tang, jieming zhu

Conformal Prediction for Time Series with Modern Hopfield Networks

Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter

Diversifying Spatial-Temporal Perception for Video Domain Generalization

Kun-Yu Lin, Jia-Run Du, Yipeng Gao, Jiaming Zhou, Wei-Shi Zheng

A Diffusion-Model of Joint Interactive Navigation

Matthew Niedoba, Jonathan Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas

Geometric Transformer with Interatomic Positional Encoding

Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng