NeurIPS 2023

3,540 papers

Equal Opportunity of Coverage in Fair Regression

Fangxin Wang, Lu Cheng, Ruocheng Guo, Kay Liu, Philip S Yu

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein

SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding

Paul-Edouard Sarlin, Eduard Trulls, Marc Pollefeys, Jan Hosang, Simon Lynen

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

Florian E. Dorner, Nikola Konstantinov, Georgi Pashaliev, Martin Vechev

Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks

Roey Magen, Ohad Shamir

Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL

Peng CHENG, Xianyuan Zhan, zhihao wu, Wenjia Zhang, Youfang Lin

VideoComposer: Compositional Video Synthesis with Motion Controllability

Xiang Wang, Hangjie Yuan, Shiwei Zhang, Dayou Chen, Jiuniu Wang

Incentives in Private Collaborative Machine Learning

Rachael Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low

Generating Behaviorally Diverse Policies with Latent Diffusion Models

Shashank Hegde, Sumeet Batra, K.R. Zentner, Gaurav Sukhatme

Collaboratively Learning Linear Models with Structured Missing Data

Chen Cheng, Gary Cheng, John C. Duchi

Encoding Human Behavior in Information Design through Deep Learning

Guanghui Yu, Wei Tang, Saumik Narayanan, Chien-Ju Ho

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Scott Pesme, Nicolas Flammarion

Balancing memorization and generalization in RNNs for high performance brain-machine Interfaces

Joseph Costello, Hisham Temmar, Luis Cubillos, Matthew Mender, Dylan Wallace

Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory

Zhibin Duan, Zhiyi Lv, Chaojie Wang, Bo Chen, Bo An

Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior

Luke Travis, Kolyan Ray

De novo Drug Design using Reinforcement Learning with Multiple GPT Agents

Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang

Towards Efficient Image Compression Without Autoregressive Models

Muhammad Salman Ali, Yeongwoong Kim, Maryam Qamar, Sung-Chang Lim, Donghyun Kim

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

Neeratyoy Mallik, Edward Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski

CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning

Charles Guille-Escuret, Pau Rodriguez, David Vázquez, Ioannis Mitliagkas, Joao Monteiro

Learning to Taste: A Multimodal Wine Dataset

Thoranna Bender, Simon Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig

Explaining Predictive Uncertainty with Information Theoretic Shapley Values

David Watson, Joshua O'Hara, Niek Tax, Richard Mudd, Ido Guy

Block-State Transformers

Jonathan Pilault, Mahan Fathi, Orhan Firat, Chris Pal, Pierre-Luc Bacon

Learning Robust Statistics for Simulation-based Inference under Model Misspecification

Daolang Huang, Ayush Bharti, Amauri Souza, Luigi Acerbi, Samuel Kaski

Fitting trees to ℓ_1-hyperbolic distances

Joon-Hyeok Yim, Anna Gilbert

ChessGPT: Bridging Policy Learning and Language Modeling

Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang

Private Distribution Learning with Public Data: The View from Sample Compression

Shai Ben-David, Alex Bie, Clément L Canonne, Gautam Kamath, Vikrant Singhal

Mask Propagation for Efficient Video Semantic Segmentation

Yuetian Weng, Mingfei Han, Haoyu He, Mingjie Li, Lina Yao

Direct Diffusion Bridge using Data Consistency for Inverse Problems

Hyungjin Chung, Jeongsol Kim, Jong Chul Ye

Entropy-based Training Methods for Scalable Neural Implicit Samplers

Weijian Luo, Boya Zhang, Zhihua Zhang

3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes

Haotian Xue, Antonio Torralba, Josh Tenenbaum, Dan Yamins, Yunzhu Li

TIES-Merging: Resolving Interference When Merging Models

Prateek Yadav, Derek Tam, Leshem Choshen, Colin A Raffel, Mohit Bansal

Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs

Dominik Straub, Matthias Schultheis, Heinz Koeppl, Constantin A Rothkopf

VanillaNet: the Power of Minimalism in Deep Learning

Hanting Chen, Yunhe Wang, Jianyuan Guo, Dacheng Tao

Finite-Time Analysis of Single-Timescale Actor-Critic

Xuyang Chen, Lin Zhao

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction

Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf

PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas

Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo, Chen Wang, Ying Shan

Compositional Generalization from First Principles

Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel

Active Negative Loss Functions for Learning with Noisy Labels

Xichen Ye, Xiaoqiang Li, songmin dai, Tong Liu, Yan Sun

Learning Modulated Transformation in GANs

Ceyuan Yang, Qihang Zhang, Yinghao Xu, Jiapeng Zhu, Yujun Shen

Zero-shot causal learning

Hamed Nilforoshan, Michael Moor, Yusuf Roohani, Yining Chen, Anja Šurina

Reconciling Competing Sampling Strategies of Network Embedding

Yuchen Yan, Baoyu Jing, Lihui Liu, Ruijie Wang, Jinning Li

Macro Placement by Wire-Mask-Guided Black-Box Optimization

Yunqi Shi, Ke Xue, Song Lei, Chao Qian

Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation

Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma

Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning

Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-bianchi, Andreas Krause

DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method

Ahmed Khaled, Konstantin Mishchenko, Chi Jin

RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization

Zhecheng Yuan, Sizhe Yang, Pu Hua, Can Chang, Kaizhe Hu

Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized Codebase

Qiuyu Wang, Zifan Shi, Kecheng Zheng, Yinghao Xu, Sida Peng

When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation

Xinhong Ma, Yiming Wang, Hao Liu, Tianyu Guo, Yunhe Wang

Data Market Design through Deep Learning

Sai Srivatsa Ravindranath, Yanchen Jiang, David C. Parkes

Efficient Activation Function Optimization through Surrogate Modeling

Garrett Bingham, Risto Miikkulainen

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen

Learning non-Markovian Decision-Making from State-only Sequences

Aoyang Qin, Feng Gao, Qing Li, Song-chun Zhu, Sirui Xie

FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning

Dipam Goswami, Yuyang Liu, Bartłomiej Twardowski, Joost van de Weijer

FLSL: Feature-level Self-supervised Learning

Qing Su, Anton Netchaev, Hai Li, Shihao Ji

One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models

Ba-Hien Tran, Giulio Franzese, Pietro Michiardi, Maurizio Filippone

Quantifying the Cost of Learning in Queueing Systems

Daniel Freund, Thodoris Lykouris, Wentao Weng

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics

Anwar Said, Roza Bayrak, Tyler Derr, Mudassir Shabbir, Daniel Moyer

Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds

Michael Crawshaw, Yajie Bao, Mingrui Liu

SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations

Ziyuan Ye, Rihan Huang, Qilin Wu, Quanying Liu

SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning

Yi-Chung Chen, Hsi-Wen Chen, Shun-Gui Wang, Ming-syan Chen

Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!

Konstantin Makarychev, Sayak Chakrabarty

Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure

Yuchao Qin, Mihaela van der Schaar, Changhee Lee

Time-uniform confidence bands for the CDF under nonstationarity

Paul Mineiro, Steven Howard

Provably Efficient Algorithm for Nonstationary Low-Rank MDPs

Yuan Cheng, Jing Yang, Yingbin Liang

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

shaokai ye, Jessy Lauer, Mu Zhou, Alexander Mathis, Mackenzie Mathis

Model-Based Control with Sparse Neural Dynamics

Ziang Liu, Genggeng Zhou, Jeff He, Tobia Marcucci, Fei-Fei Li

The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance

Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward Browne

Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss

An Zhang, Leheng Sheng, Zhibo Cai, Xiang Wang, Tat-Seng Chua

Tracking Most Significant Shifts in Nonparametric Contextual Bandits

Joe Suk, Samory Kpotufe

Nonparametric Boundary Geometry in Physics Informed Deep Learning

Scott Cameron, Arnu Pretorius, S Roberts

Memory-Constrained Algorithms for Convex Optimization

Moise Blanchard, Junhui Zhang, Patrick Jaillet

On the Implicit Bias of Linear Equivariant Steerable Networks

Ziyu Chen, Wei Zhu

Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem

Jincheng Cao, Ruichen Jiang, Nazanin Abolfazli, Erfan Yazdandoost Hamedani, Aryan Mokhtari

Truly Scale-Equivariant Deep Nets with Fourier Layers

Md Ashiqur Rahman, Raymond A. Yeh

Auditing Fairness by Betting

Ben Chugg, Santiago Cortes-Gomez, Bryan Wilder, Aaditya Ramdas

Visual Programming for Step-by-Step Text-to-Image Generation and Evaluation

Jaemin Cho, Abhay Zala, Mohit Bansal

Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data

Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu

Graph of Circuits with GNN for Exploring the Optimal Design Space

Aditya Shahane, Saripilli Swapna Manjiri, Ankesh Jain, Sandeep Kumar

Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis

Victor Letzelter, Mathieu Fontaine, Mickaël Chen, Patrick Pérez, Slim Essid

On student-teacher deviations in distillation: does it pay to disobey?

Vaishnavh Nagarajan, Aditya K Menon, Srinadh Bhojanapalli, Hossein Mobahi, Sanjiv Kumar

Binary Classification with Confidence Difference

Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-ling Zhang

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management

Dhawal Gupta, Yinlam Chow, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier

GEX: A flexible method for approximating influence via Geometric Ensemble

SungYub Kim, Kyungsu Kim, Eunho Yang

GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning

Haiteng Zhao, Shengchao Liu, Ma Chang, Hannan Xu, Jie Fu

Don’t Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner

Zhengxiang Shi, Aldo Lipani

Learning Shared Safety Constraints from Multi-task Demonstrations

Konwoo Kim, Gokul Swamy, ZUXIN LIU, Ding Zhao, Sanjiban Choudhury

Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives

Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei Efros, Mathieu Aubry

Contextually Affinitive Neighborhood Refinery for Deep Clustering

Chunlin Yu, Ye Shi, Jingya Wang

LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections

Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei LIN, Horst Possegger, Mateusz Kozinski

Federated Conditional Stochastic Optimization

Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang

Budgeting Counterfactual for Offline RL

Yao Liu, Pratik Chaudhari, Rasool Fakoor

Normalization-Equivariant Neural Networks with Application to Image Denoising

Sébastien Herbreteau, Emmanuel Moebel, Charles Kervrann

Exact Verification of ReLU Neural Control Barrier Functions

Hongchao Zhang, Junlin Wu, Yevgeniy Vorobeychik, Andrew Clark

Formalizing locality for normative synaptic plasticity models

Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake Richards, Guillaume Lajoie

Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset

Saeid Alavi Naeini, Raeid Saqur, Mozhgan Saeidi, John Giorgi, Babak Taati

Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning

Jing Zhang, Chi Zhang, Wenjia Wang, Bing-Yi Jing, Bingyi Jing

Non-autoregressive Machine Translation with Probabilistic Context-free Grammar

Shangtong Gui, Chenze Shao, Zhengrui Ma, xishan zhang, Yunji Chen

Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions

Ruofan Wu, Jiawei Qiao, Mingzhe Wu, Wen Yu, Ming Zheng

OpenAGI: When LLM Meets Domain Experts

Yingqiang Ge, Wenyue Hua, Kai Mei, jianchao ji, Juntao Tan

CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders

Anthony Fuller, Koreen Millard, James Green