NeurIPS

EHRTutor: Enhancing Patient Understanding of Discharge Instructions

Zihao Zhang, Zonghai Yao, Huixue Zhou, Feiyun ouyang, Hong Yu

Comments To appear in NeurIPS'23 Workshop on Generative AI for Education (GAIED)

Fast Trainable Projection for Robust Fine-Tuning

Junjiao Tian, Yen-Cheng Liu, James Seale Smith, Zsolt Kira

Comments Accepted to NeurIPS 2023

MAG-GNN: Reinforcement Learning Boosted Graph Neural Network

Lecheng Kong, Jiarui Feng, Hao Liu, Dacheng Tao, Yixin Chen, Muhan Zhang

Comments Accepted to NeurIPS 2023

Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations

Piotr Indyk, Haike Xu

Comments Accepted by NeurIPS 2023

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming

Gregory Dexter, Petros Drineas, David P. Woodruff, Taisuke Yasuda

Comments To appear in NeurIPS 2023

Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations

Jungtaek Kim, Mingxuan Li, Oliver Hinder, Paul W. Leu

Comments 31 pages, 31 figures, 4 tables. Accepted at the 37th Conference on Neural Information Processing Systems (NeurIPS 2023), Datasets and Benchmarks Track

Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng

Comments NeurIPS 2023, 34 pages, 35 figures

Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction

Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu, Thomas H. Li, Bohan Zhuang, Mingkui Tan

Comments Accepted by 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation

Fei Zhang, Tianfei Zhou, Boyang Li, Hao He, Chaofan Ma, Tianjiao Zhang, Jiangchao Yao, Ya Zhang, Yanfeng Wang

Comments 14 pages, Accept in NeurIPS 2023

A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning

Alicia Curth, Alan Jeffares, Mihaela van der Schaar

Comments To appear in the Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

TRIAGE: Characterizing and auditing training data for improved regression

Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar

Comments Presented at NeurIPS 2023

Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses

Elena Sizikova, Niloufar Saharkhiz, Diksha Sharma, Miguel Lago, Berkman Sahiner, Jana G. Delfino, Aldo Badano

Comments NeurIPS 2023 Datasets and Benchmarks Track

Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning

Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Gaetan Lin, Hao Chen, Liwei Wu, Ning Jia, Shiji Song, Gao Huang

Comments NeurIPS 2023 spotlight. 24 pages, 13 figures

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, Xiuqiang He, Xue Liu

Comments NeurIPS 2023 poster

Equivariant Adaptation of Large Pretrained Models

Arnab Kumar Mondal, Siba Smarak Panigrahi, Sékou-Oumar Kaba, Sai Rajeswar, Siamak Ravanbakhsh

Comments 17 pages, 6 figures. Accepted to NeurIPS 2023

Accelerating Motion Planning via Optimal Transport

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

Comments Published as a conference paper at NeurIPS 2023. Project website: https://sites.google.com/view/sinkhorn-step/

ADGym: Design Choices for Deep Anomaly Detection

Minqi Jiang, Chaochuan Hou, Ao Zheng, Songqiao Han, Hailiang Huang, Qingsong Wen, Xiyang Hu, Yue Zhao

Comments NeurIPS 2023. The first three authors contribute equally. Code available at https://github.com/Minqi824/ADGym

ODE-based Recurrent Model-free Reinforcement Learning for POMDPs

Xuanle Zhao, Duzhen Zhang, Liyuan Han, Tielin Zhang, Bo Xu

Comments Accepted by NeurIPS 2023

Physics-Driven ML-Based Modelling for Correcting Inverse Estimation

Ruiyuan Kang, Tingting Mu, Panos Liatsis, Dimitrios C. Kyritsis

Comments 19 pages, the paper is accepted by Neurips 2023 as a spotlight

Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck

Benjamin L. Edelman, Surbhi Goel, Sham Kakade, Eran Malach, Cyril Zhang

Comments v2: NeurIPS 2023 camera-ready updates

Complexity Matters: Rethinking the Latent Space for Generative Modeling

Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li

Comments Accepted to NeurIPS 2023 (Spotlight)

Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics

Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty

Comments Main: 10 pages,4 Figures Tables Supplementary: 19 pages, 13 Figures ,1 Table. Sumbitted to Neurips 2023

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

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

Comments Accepted at NeurIPS 2023

OpenMask3D: Open-Vocabulary 3D Instance Segmentation

Ayça Takmaz, Elisabetta Fedele, Robert W. Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann

Comments NeurIPS 2023. Project page: https://openmask3d.github.io/

Journal ref NeurIPS 2023

Block-State Transformers

Mahan Fathi, Jonathan Pilault, Orhan Firat, Christopher Pal, Pierre-Luc Bacon, Ross Goroshin

Comments NeurIPS'23 - Thirty-seventh Conference on Neural Information Processing Systems

Neural Fields with Hard Constraints of Arbitrary Differential Order

Fangcheng Zhong, Kyle Fogarty, Param Hanji, Tianhao Wu, Alejandro Sztrajman, Andrew Spielberg, Andrea Tagliasacchi, Petra Bosilj, Cengiz Oztireli

Comments 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation

Thomas Fel, Victor Boutin, Mazda Moayeri, Rémi Cadène, Louis Bethune, Léo andéol, Mathieu Chalvidal, Thomas Serre

Journal ref Conference on Neural Information Processing Systems (NeurIPS), 2023

TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials

Guillem Simeon, Gianni de Fabritiis

Comments NeurIPS 2023, camera-ready version

Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models

Siyan Zhao, Aditya Grover

Comments published at NeurIPS 2023, project page: https://siyan-zhao.github.io/decision-stacks/

Topology-Aware Uncertainty for Image Segmentation

Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen

Comments Accepted to NeurIPS 2023; 22 pages, 14 figures, 6 tables