NeurIPS

Diffusion based Zero-shot Medical Image-to-Image Translation for Cross Modality Segmentation

Zihao Wang, Yingyu Yang, Yuzhou Chen, Tingting Yuan, Maxime Sermesant, Herve Delingette, Ona Wu

Comments Neurips 2023 Diffusion Workshop

Policy-Guided Diffusion

Matthew Thomas Jackson, Michael Tryfan Matthews, Cong Lu, Benjamin Ellis, Shimon Whiteson, Jakob Foerster

Comments Previously at the NeurIPS 2023 Workshop on Robot Learning

Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu, Tao Lei, Iftekhar Naim, Ming-Wei Chang, Vincent Y. Zhao

Comments NeurIPS 2023. Code available at https://github.com/google-deepmind/xtr

Percentile Criterion Optimization in Offline Reinforcement Learning

Elita A. Lobo, Cyrus Cousins, Yair Zick, Marek Petrik

Comments Accepted at Neurips 2023

On the Learnability of Out-of-distribution Detection

Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu

Comments Accepted by JMLR in 7th of April, 2024. This is a journal extension of the previous NeurIPS 2022 Outstanding Paper "Is Out-of-distribution Detection Learnable?" [arXiv:2210.14707]

Measurement in the Age of LLMs: An Application to Ideological Scaling

Sean O'Hagan, Aaron Schein

Comments Under review a Harvard Data Science Review. Previously presented at the 4th International Conference of Social Computing in Beijing, China, September 2023, the New Directions in Analyzing Text as Data (TADA) meeting in Amherst, MA, USA, November 2023, and the NeurIPS workshop titled "I Can't Believe It's Not Better!'' Failure Modes in the Age of Foundation Models in New Orleans, LA, December 2023

Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction

Anagh Malik, Parsa Mirdehghan, Sotiris Nousias, Kiriakos N. Kutulakos, David B. Lindell

Comments NeurIPS 2023, Project Page: https://anaghmalik.com/TransientNeRF/

PCF-GAN: generating sequential data via the characteristic function of measures on the path space

Hang Lou, Siran Li, Hao Ni

Journal ref Advances in Neural Information Processing Systems 36 (2024)

Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection

Hezhe Qiao, Guansong Pang

Comments Accepted at NeurIPS 2023

Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes

Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang

Comments Published at NeurIPS 2023. Code is available at https://github.com/rishibommasani/EcosystemLevelAnalysis

Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery

Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś

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

Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional Communication

Łukasz Kuciński, Tomasz Korbak, Paweł Kołodziej, Piotr Miłoś

Comments NeurIPS 2021

Hybrid physics-based and data-driven modeling with calibrated uncertainty for lithium-ion battery degradation diagnosis and prognosis

Jing Lin, Yu Zhang, Edwin Khoo

Comments 6 pages, 3 figures, accepted for poster presentation at Tackling Climate Change with Machine Learning workshop at NeurIPS 2021

Journal ref NeurIPS 2021 Workshop on Tackling Climate Change with Machine Learning

Subgoal Search For Complex Reasoning Tasks

Konrad Czechowski, Tomasz Odrzygóźdź, Marek Zbysiński, Michał Zawalski, Krzysztof Olejnik, Yuhuai Wu, Łukasz Kuciński, Piotr Miłoś

Comments NeurIPS 2021

MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators

Jinyoung Choi, Bohyung Han

Comments NeurIPS 2022

On-Demand Sampling: Learning Optimally from Multiple Distributions

Nika Haghtalab, Michael I. Jordan, Eric Zhao

Comments 28 pages, 1 figure. Authors are ordered alphabetically. Outstanding paper award at the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022). Version v2 updates a minor mistake in Lemma 3.1

On-Device Training Under 256KB Memory

Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han

Comments NeurIPS 2022

Incentives in Private Collaborative Machine Learning

Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

Comments Accepted to NeurIPS 2023

GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection

Namyong Park, Ryan Rossi, Xing Wang, Antoine Simoulin, Nesreen Ahmed, Christos Faloutsos

Comments NeurIPS 2023

Kiki or Bouba? Sound Symbolism in Vision-and-Language Models

Morris Alper, Hadar Averbuch-Elor

Comments Accepted to NeurIPS 2023 (spotlight). Project webpage: https://kiki-bouba.github.io/

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

Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne

Comments Appeared in NeurIPS 2023 as a spotlight paper

Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondence

Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, Trevor Darrell

Comments NeurIPS 2023

SOAR: Improved Indexing for Approximate Nearest Neighbor Search

Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar

Journal ref Advances in Neural Information Processing Systems 36 (2023) 3189-3204

Scale Alone Does not Improve Mechanistic Interpretability in Vision Models

Roland S. Zimmermann, Thomas Klein, Wieland Brendel

Comments Spotlight at NeurIPS 2023. The first two authors contributed equally. Code available at https://brendel-group.github.io/imi/

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities

Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines

Comments Appears in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023). 41 pages, 3 algorithms, 2 tables

Journal ref https://proceedings.neurips.cc/paper_files/paper/2023/hash/8c3e38ce55a0fa44bc325bc6fdb7f4e5-Abstract-Conference.html

Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities

Aleksandr Beznosikov, Martin Takáč, Alexander Gasnikov

Comments Appears in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (https://proceedings.neurips.cc/paper_files/paper/2023/hash/5b4a459db23e6db9be2a128380953d96-Abstract-Conference.html). 36 pages, 3 algorithms, 1 figure, 1 table

Online Convex Optimization with Unbounded Memory

Raunak Kumar, Sarah Dean, Robert Kleinberg

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

Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic

Yufeng Zhang, Siyu Chen, Zhuoran Yang, Michael I. Jordan, Zhaoran Wang

Comments 41 pages, accepted to NeurIPS 2021, add acknowledgement

Making Batch Normalization Great in Federated Deep Learning

Jike Zhong, Hong-You Chen, Wei-Lun Chao

Comments An extended version of the workshop paper in NeurIPS 2023 (https://federated-learning.org/fl@fm-neurips-2023/)

A Simple yet Effective Framework for Active Learning to Rank

Qingzhong Wang, Haifang Li, Haoyi Xiong, Wen Wang, Jiang Bian, Yu Lu, Shuaiqiang Wang, Zhicong Cheng, Dejing Dou, Dawei Yin

Comments This paper is accepted to Machine Intelligence Research and a short version is presented in NeurIPS 2022 Workshop on Human in the Loop Learning