NeurIPS 2023

3,540 papers

Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory

Ankur Sikarwar, Mengmi Zhang

State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory

Shida Wang, Beichen Xue

Inner Product-based Neural Network Similarity

Wei Chen, Zichen Miao, Qiang Qiu

Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance

Jiaming Qiu, Xiongtao Dai

Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation

Zibo Zhao, Wen Liu, Xin Chen, Xianfang Zeng, Rui Wang

Squared Neural Families: A New Class of Tractable Density Models

Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification

Mintong Kang, Dawn Song, Bo Li

Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL

Zhiwei Xu, Bin Zhang, Dapeng Li, Guangchong Zhou, Zeren Zhang

Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder

Huiwon Jang, Jihoon Tack, Daewon Choi, Jongheon Jeong, Jinwoo Shin

Gaussian Membership Inference Privacy

Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci

Learning Functional Transduction

Mathieu Chalvidal, Thomas Serre, Rufin VanRullen

Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift

Xingdong Feng, XIN HE, Caixing Wang, Chao Wang, Jingnan Zhang

k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy

Chenglin Fan, Ping Li, Xiaoyun Li

Implicit Variational Inference for High-Dimensional Posteriors

Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter Boomsma, Jes Frellsen

TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion

Preetha Vijayan, Prashant Bhat, Bahram Zonooz, Elahe Arani

Model-free Posterior Sampling via Learning Rate Randomization

Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos

Uncertainty-Aware Instance Reweighting for Off-Policy Learning

Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie, Yang Liu

A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes

Han Zhong, Tong Zhang

Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation

Fei Zhang, Tianfei Zhou, Boyang Li, Hao He, Chaofan Ma

Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser

Yung-Hsuan Lai, Yen-Chun Chen, Frank Wang

Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering

Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin Renqiang Min

Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective

Zeyuan Yin, Eric P. Xing, Zhiqiang Shen

Tailoring Self-Attention for Graph via Rooted Subtrees

Siyuan Huang, Yunchong Song, Jiayue Zhou, Zhouhan Lin

Effective Robustness against Natural Distribution Shifts for Models with Different Training Data

Zhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-jui Hsieh

Contrastive Sampling Chains in Diffusion Models

Junyu Zhang, Daochang Liu, Shichao Zhang, Chang Xu

The Behavior and Convergence of Local Bayesian Optimization

Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob Gardner

ReMaX: Relaxing for Better Training on Efficient Panoptic Segmentation

Shuyang Sun, WEIJUN WANG, Andrew Howard, Qihang Yu, Philip Torr

Alignment with human representations supports robust few-shot learning

Ilia Sucholutsky, Tom Griffiths

Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning

Akhil Bagaria, Ben Abbatematteo, Omer Gottesman, Matt Corsaro, Sreehari Rammohan

Connecting Certified and Adversarial Training

Yuhao Mao, Mark Müller, Marc Fischer, Martin Vechev

Cross-Domain Policy Adaptation via Value-Guided Data Filtering

Kang Xu, Chenjia Bai, Xiaoteng Ma, Dong Wang, Bin Zhao

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks

Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, Rodrigo Perez-Vicente, Lucas Willems

BanditPAM++: Faster k-medoids Clustering

Mo Tiwari, Ryan Kang, Donghyun Lee, Sebastian Thrun, Ilan Shomorony

Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity

Jian-Feng CAI, Jose Vinicius de Miranda Cardoso, Daniel Palomar, Jiaxi Ying

Swarm Reinforcement Learning for Adaptive Mesh Refinement

Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger

What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation

Benedikt Blumenstiel, Johannes Jakubik, Hilde Kuehne, Michael Vössing

Covariance-adaptive best arm identification

El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen

Learning to Augment Distributions for Out-of-distribution Detection

qizhou wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li

FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout

Irene Wang, Prashant Nair, Divya Mahajan

Collaborative Score Distillation for Consistent Visual Editing

Subin Kim, Kyungmin Lee, June Suk Choi, Jongheon Jeong, Kihyuk Sohn

Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition

Xiwen WANG, Jiaxi Ying, Daniel Palomar

Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots

Ruixiang (Ryan) Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen

Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision

Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen

How to Scale Your EMA

Dan Busbridge, Jason Ramapuram, Pierre Ablin, Tatiana Likhomanenko, Eeshan Gunesh Dhekane

Are Vision Transformers More Data Hungry Than Newborn Visual Systems?

Lalit Pandey, Samantha Wood, Justin Wood

StyleGAN knows Normal, Depth, Albedo, and More

Anand Bhattad, Daniel McKee, Derek Hoiem, David A. Forsyth

TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph

Xueyuan Lin, Haihong E, Chengjin Xu, Gengxian Zhou, Haoran Luo

Successor-Predecessor Intrinsic Exploration

Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel J Gershman

Formulating Discrete Probability Flow Through Optimal Transport

Pengze Zhang, Hubery Yin, Chen Li, Xiaohua Xie

Scaling Open-Vocabulary Object Detection

Matthias Minderer, Alexey Gritsenko, Neil Houlsby

Inserting Anybody in Diffusion Models via Celeb Basis

Ge Yuan, Xiaodong Cun, Yong Zhang, Maomao Li, Chenyang Qi

STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events

Kazuki Shimada, Archontis Politis, Parthasaarathy Sudarsanam, Daniel A. Krause, Kengo Uchida

Facing Off World Model Backbones: RNNs, Transformers, and S4

Fei Deng, Junyeong Park, Sungjin Ahn

Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective

Huayang Li, Tian Lan, Zihao Fu, Deng Cai, Lemao Liu

Bayesian Learning via Q-Exponential Process

Shuyi Li, Michael O'Connor, Shiwei Lan

VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset

Sihan Chen, Handong Li, Qunbo Wang, Zijia Zhao, Mingzhen Sun

Training Chain-of-Thought via Latent-Variable Inference

Du Phan, Matthew Douglas Hoffman, David Dohan, Sholto Douglas, Tuan Anh Le

Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery

Sarah Rastegar, Hazel Doughty, Cees Snoek

Survival Permanental Processes for Survival Analysis with Time-Varying Covariates

Hideaki Kim

Deep Fractional Fourier Transform

Hu Yu, Jie Huang, Lingzhi LI, man zhou, Feng Zhao

May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations

Rui Feng, Qi Zhu, Huan Tran, Binghong Chen, Aubrey Toland

Responsible AI (RAI) Games and Ensembles

Yash Gupta, Runtian Zhai, Arun Suggala, Pradeep K Ravikumar, Pradeep K. Ravikumar

Bicriteria Approximation Algorithms for the Submodular Cover Problem

Wenjing Chen, Victoria Crawford

HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation

Ho Man Kwan, Ge Gao, Fan Zhang, Andrew Gower, David Bull

Approximate inference of marginals using the IBIA framework

Shivani Bathla, Vinita Vasudevan

AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation

Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel

Learning Large-scale Neural Fields via Context Pruned Meta-Learning

Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin

DASpeech: Directed Acyclic Transformer for Fast and High-quality Speech-to-Speech Translation

Qingkai Fang, Yan Zhou, Yang Feng

Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning

Fangchen Yu, Runze Zhao, Zhan Shi, Yiwen Lu, Jicong Fan

Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time

Xinyuan Cao, Santosh Vempala

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini

A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning

Nika Haghtalab, Michael I. Jordan, Eric Zhao

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang

Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack

Pratik Karmakar, Debabrota Basu

Grassmann Manifold Flows for Stable Shape Generation

Ryoma Yataka, Kazuki Hirashima, Masashi Shiraishi

Why Does Sharpness-Aware Minimization Generalize Better Than SGD?

Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-jui Hsieh

Resetting the Optimizer in Deep RL: An Empirical Study

Kavosh Asadi, Rasool Fakoor, Shoham Sabach

Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction

Yuanhao Wang, Ramzi Idoughi, Wolfgang Heidrich

Data Minimization at Inference Time

Cuong Tran, Ferdinando Fioretto

Bias in Evaluation Processes: An Optimization-Based Model

L. Elisa Celis, Amit Kumar, Anay Mehrotra, Nisheeth K. Vishnoi

Dynamic Personalized Federated Learning with Adaptive Differential Privacy

Xiyuan Yang, Wenke Huang, Mang Ye

Clustering the Sketch: Dynamic Compression for Embedding Tables

Henry Tsang, Thomas Ahle

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He

Robust covariance estimation with missing values and cell-wise contamination

Grégoire Pacreau, Karim Lounici

Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources

Haotian Zheng, qizhou wang, Zhen Fang, Xiaobo Xia, Feng Liu

Language Is Not All You Need: Aligning Perception with Language Models

Shaohan Huang, Li Dong, Wenhui Wang, Yaru Hao, Saksham Singhal

When Does Optimizing a Proper Loss Yield Calibration?

Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran

The s-value: evaluating stability with respect to distributional shifts

Suyash Gupta, Dominik Rothenhäusler

In-Context Impersonation Reveals Large Language Models' Strengths and Biases

Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, Zeynep Akata

Systematic Visual Reasoning through Object-Centric Relational Abstraction

Taylor Webb, Shanka Subhra Mondal, Jonathan D. Cohen, Jonathan D Cohen

Reinforcement Learning with Fast and Forgetful Memory

Steven Morad, Ryan Kortvelesy, Stephan Liwicki, Amanda Prorok

GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction

Rui Yang, Lin Song, Yanwei Li, Sijie Zhao, Yixiao Ge

Stein Π-Importance Sampling

Congye Wang, Ye Chen, Heishiro Kanagawa, Chris J Oates

Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer

Yuandong Tian, Yiping Wang, Beidi Chen, Simon S Du

Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy

Aahlad Manas Puli, Lily Zhang, Yoav Wald, Rajesh Ranganath

CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object Detection

Yang Cao, Zeng Yihan, Hang Xu, Dan Xu

Error Bounds for Learning with Vector-Valued Random Features

Samuel Lanthaler, Nicholas H. Nelsen

Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares

Christian Kümmerle, Johannes Maly

Resilient Constrained Learning

Ignacio Hounie, Alejandro Ribeiro, Luiz F. O. Chamon

Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity

Tianqin Li, Ziqi Wen, Yangfan Li, Tai Sing Lee