NeurIPS

Generative Nowcasting of Marine Fog Visibility in the Grand Banks area and Sable Island in Canada

Eren Gultepe, Sen Wang, Byron Blomquist, Harindra J. S. Fernando, O. Patrick Kreidl, David J. Delene, Ismail Gultepe

Journal ref Tackling Climate Change with Machine Learning: workshop at NeurIPS 2023

Latent Space Translation via Semantic Alignment

Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolà

Comments Accepted at NeurIPS 2023. 21 pages, 13 figures, 8 tables

Denoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planning

Junwoo Chang, Hyunwoo Ryu, Jiwoo Kim, Soochul Yoo, Jongeun Choi, Joohwan Seo, Nikhil Prakash, Roberto Horowitz

Comments 9 pages, 6 figures

Journal ref NeurIPS 2023 Workshop on Diffusion Models

PGraphDTA: Improving Drug Target Interaction Prediction using Protein Language Models and Contact Maps

Rakesh Bal, Yijia Xiao, Wei Wang

Comments AI for Science Workshop, NeurIPS 2023. 11 pages, 5 figures, 4 tables

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

Zeyuan Yin, Eric Xing, Zhiqiang Shen

Comments NeurIPS 2023 spotlight. Code at https://github.com/VILA-Lab/SRe2L

Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing

Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan

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

Safe Active Learning for Time-Series Modeling with Gaussian Processes

Christoph Zimmer, Mona Meister, Duy Nguyen-Tuong

Comments Clarification / Errata of article originally published at NeurIPS: https://proceedings.neurips.cc/paper/2018/hash/b197ffdef2ddc3308584dce7afa3661b-Abstract.html

Benchmarking Distribution Shift in Tabular Data with TableShift

Josh Gardner, Zoran Popovic, Ludwig Schmidt

Comments NeurIPS 2023 Dataset and Benchmarks Track accepted version

Template-free Articulated Neural Point Clouds for Reposable View Synthesis

Lukas Uzolas, Elmar Eisemann, Petr Kellnhofer

Journal ref Thirty-seventh Conference on Neural Information Processing Systems, 2023

Learning Interpretable Low-dimensional Representation via Physical Symmetry

Xuanjie Liu, Daniel Chin, Yichen Huang, Gus Xia

Comments Accepted by NeurIPS 2023

FlowPG: Action-constrained Policy Gradient with Normalizing Flows

Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar

Journal ref Thirty-seventh Conference on Neural Information Processing Systems. 2023

Multi-Task Learning with Summary Statistics

Parker Knight, Rui Duan

Comments NeurIPS 2023, final version

Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning

Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal

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

Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures

David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Bakke Botnan, Steve Oudot

Comments 26 pages, 4 figures, 9 tables; v2: final version in NeurIPS 2023

Interpretability at Scale: Identifying Causal Mechanisms in Alpaca

Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman

Comments NeurIPS 2023 with Author Corrections

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance

Ted Fujimoto, Joshua Suetterlein, Samrat Chatterjee, Auroop Ganguly

Comments Poster at the Workshop on Regulatable Machine Learning at the 37th Conference on Neural Information Processing Systems (RegML @ NeurIPS 2023)

Reinforcement-learning robotic sailboats: simulator and preliminary results

Eduardo Charles Vasconcellos, Ronald M Sampaio, André P D Araújo, Esteban Walter Gonzales Clua, Philippe Preux, Raphael Guerra, Luiz M G Gonçalves, Luis Martí, Hernan Lira, Nayat Sanchez-Pi

Journal ref NeurIPS 2023 Workshop on Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models, Dec 2023, New Orelans, United States

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond

Thanh Nguyen-Tang, Raman Arora

Comments NeurIPS'23; Arxiv is the authors' preferred version; v2: add a missing related work

Language Model Training Paradigms for Clinical Feature Embeddings

Yurong Hu, Manuel Burger, Gunnar Rätsch, Rita Kuznetsova

Comments Poster at "NeurIPS 2023 Workshop: Self-Supervised Learning - Theory and Practice"

VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models

Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma

Comments Accepted by NeurIPS 2023, 21 pages

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition

Meena Jagadeesan, Michael I. Jordan, Jacob Steinhardt, Nika Haghtalab

Comments Appeared at NeurIPS 2023; this is the full version

HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

Shengcao Cao, Dhiraj Joshi, Liang-Yan Gui, Yu-Xiong Wang

Comments NeurIPS 2023

Minimum Description Length and Generalization Guarantees for Representation Learning

Milad Sefidgaran, Abdellatif Zaidi, Piotr Krasnowski

Comments Accepted and presented at NeurIPS 2023

Homograph Attacks on Maghreb Sentiment Analyzers

Fatima Zahra Qachfar, Rakesh M. Verma

Comments NAML, North Africans in Machine Leaning, NeurIPS, Neural Information Processing Systems

Anytime-Competitive Reinforcement Learning with Policy Prior

Jianyi Yang, Pengfei Li, Tongxin Li, Adam Wierman, Shaolei Ren

Comments Accepted by NeurIPS 2023

Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models

Andy Zhou, Jindong Wang, Yu-Xiong Wang, Haohan Wang

Comments Published in NeurIPS 2023

Ultra Fast Transformers on FPGAs for Particle Physics Experiments

Zhixing Jiang, Dennis Yin, Elham E Khoda, Vladimir Loncar, Ekaterina Govorkova, Eric Moreno, Philip Harris, Scott Hauck, Shih-Chieh Hsu

Comments 6 pages, 2 figures

Journal ref Machine Learning and the Physical Sciences Workshop, NeurIPS 2023

I Prefer not to Say: Protecting User Consent in Models with Optional Personal Data

Tobias Leemann, Martin Pawelczyk, Christian Thomas Eberle, Gjergji Kasneci

Comments v5: AAAI-24 Camera-Ready Version Including Appendices. v1: NeurIPS 2022 Workshop on Algorithmic Fairness through the Lens of Causality and Privacy (AFCP)

On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective

Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin

Journal ref Conference on Neural Information Processing Systems (NeurIPS), Neural Information Processing Systems Foundation, Dec 2023, New Orleans (Louisiana), United States

Measures of Information Reflect Memorization Patterns

Rachit Bansal, Danish Pruthi, Yonatan Belinkov

Comments 22 pages; NeurIPS 2022. Code and data at https://rachitbansal.github.io/information-measures