NeurIPS

Clifford Group Equivariant Neural Networks

David Ruhe, Johannes Brandstetter, Patrick Forré

Comments Published at NeurIPS 2023 (Oral)

Paxion: Patching Action Knowledge in Video-Language Foundation Models

Zhenhailong Wang, Ansel Blume, Sha Li, Genglin Liu, Jaemin Cho, Zineng Tang, Mohit Bansal, Heng Ji

Comments NeurIPS 2023 spotlight

Conformalized matrix completion

Yu Gui, Rina Foygel Barber, Cong Ma

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

Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation

Myong Chol Jung, He Zhao, Joanna Dipnall, Lan Du

Comments Accepted to NeurIPS 2023

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach

Zhimeng Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu

Comments NeurIPS 2023

Evaluating Physically Motivated Loss Functions for Photometric Redshift Estimation

Andrew Engel, Jan Strube

Comments Preliminary Report; Submitted to Neurips 2023 as Workshop Paper

ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection

Zhongzhan Huang, Pan Zhou, Shuicheng Yan, Liang Lin

Comments accepted by NeurIPS 2023

NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding

Ming Hu, Lin Wang, Siyuan Yan, Don Ma, Qingli Ren, Peng Xia, Wei Feng, Peibo Duan, Lie Ju, Zongyuan Ge

Comments Accepted by NeurIPS 2023 Datasets and Benchmarks Track

FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery

Anatol Garioud, Nicolas Gonthier, Loic Landrieu, Apolline De Wit, Marion Valette, Marc Poupée, Sébastien Giordano, Boris Wattrelos

Comments NeurIPS 2023 - Datasets & Benchmarks Track

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos Psaros, Kenji Kawaguchi

Comments Accepted at NeurIPS 2023. Code is available at https://github.com/ShenQianli/PICProp

Full-Atom Protein Pocket Design via Iterative Refinement

Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu

Comments NeurIPS 2023 Spotlight

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

Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O-Kil Kwon, Edward Choi

Comments Published as a conference paper at NeurIPS 2023 (Track on Datasets and Benchmarks)

VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation

Zekun Qi, Muzhou Yu, Runpei Dong, Kaisheng Ma

Comments Accepted at NeurIPS 2023

Elastic Decision Transformer

Yueh-Hua Wu, Xiaolong Wang, Masashi Hamaya

Comments Accepted to NeurIPS 2023

Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations

Hyeonjeong Ha, Minseon Kim, Sung Ju Hwang

Comments NeurIPS 2023, Code is available at https://github.com/HyeonjeongHa/CRoZe

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

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

Comments NeurIPS 2023

Language Model Tokenizers Introduce Unfairness Between Languages

Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, Adel Bibi

Comments Published at NeurIPS 2023, Project webpage: https://aleksandarpetrov.github.io/tokenization-fairness, Code: https://github.com/AleksandarPetrov/tokenization-fairness

DataComp: In search of the next generation of multimodal datasets

Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt

Comments NeurIPS 2023 Datasets and Benchmarks Track

Adaptive Selective Sampling for Online Prediction with Experts

Rui M. Castro, Fredrik Hellström, Tim van Erven

Journal ref NeurIPS 2023

On the Overlooked Structure of Stochastic Gradients

Zeke Xie, Qian-Yuan Tang, Mingming Sun, Ping Li

Comments NeurIPS 2023. 20 pages, 16 figures, 17 Tables; Key Words: Deep Learning, Stochastic Gradient, Optimization. arXiv admin note: text overlap with arXiv:2201.13011

Trade-off Between Efficiency and Consistency for Removal-based Explanations

Yifan Zhang, Haowei He, Zhiquan Tan, Yang Yuan

Comments NeurIPS 2023. Code: https://github.com/trusty-ai/efficient-consistent-explanation

CLIFT: Analysing Natural Distribution Shift on Question Answering Models in Clinical Domain

Ankit Pal

Comments Accepted at NeurIPS 2022 (Robustness in Sequence Modeling)

Journal ref 36th Conference on Neural Information Processing Systems, Robustness in Sequence Modeling (NeurIPS 2022)

Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

Lingbing Guo, Weiqing Wang, Zhuo Chen, Ningyu Zhang, Zequn Sun, Yixuan Lai, Qiang Zhang, Huajun Chen

Comments NeurIPS 2023 (spotlight)

A Scalable Technique for Weak-Supervised Learning with Domain Constraints

Sudhir Agarwal, Anu Sreepathy, Lalla Mouatadid

Comments 6 pages, 4 figures. Accepted at NeurIPS 2022 Workshop "Has it trained yet"

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

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

Comments Accepted by NeurIPS 2023

Provable Guarantees for Neural Networks via Gradient Feature Learning

Zhenmei Shi, Junyi Wei, Yingyu Liang

Comments NeurIPS 2023, 71 pages

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm

Haizhou Shi, Hao Wang

Comments Accepted at NeurIPS 2023

Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT

Zhen Zhang, Bingqiao Luo, Shengliang Lu, Bingsheng He

Comments Accepted by NeurIPS 2023, Datasets and Benchmarks Track

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

Xingdong Feng, Xin He, Caixing Wang, Chao Wang, Jingnan Zhang

Comments Poster to appear in Thirty-seventh Conference on Neural Information Processing Systems

A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment

Yixuan Even Xu, Steven Jecmen, Zimeng Song, Fei Fang

Comments 24 pages, 8 figures, 3 tables, neurips 2023 spotlight