NeurIPS

Most Activation Functions Can Win the Lottery Without Excessive Depth

Rebekka Burkholz

Comments Accepted for publication at NeurIPS 2022

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William Gray-Roncal, Erik C. Johnson, Eva L. Dyer

Comments 10 pages, 4 figures, Accepted at NeurIPS 2022

How Powerful are K-hop Message Passing Graph Neural Networks

Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang

Comments Accepted to NeurIPS 2022

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs

Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein

Comments Accepted to NeurIPS 2022. Contains 29 pages, 10 figures

DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning

Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah Goodman

Comments NeurIPS 2021

InsPro: Propagating Instance Query and Proposal for Online Video Instance Segmentation

Fei He, Haoyang Zhang, Naiyu Gao, Jian Jia, Yanhu Shan, Xin Zhao, Kaiqi Huang

Comments NeurIPS 2022

Emergent collective intelligence from massive-agent cooperation and competition

Hanmo Chen, Stone Tao, Jiaxin Chen, Weihan Shen, Xihui Li, Chenghui Yu, Sikai Cheng, Xiaolong Zhu, Xiu Li

Comments Published at NeurIPS 2022 Deep RL workshop. Code available at https://github.com/hanmochen/lux-open

Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits

Ruibo Liu, Chenyan Jia, Ge Zhang, Ziyu Zhuang, Tony X Liu, Soroush Vosoughi

Comments In proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

Denoising Deep Generative Models

Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini

Comments NeurIPS 2022 ICBINB workshop (spotlight)

Robust Imitation via Mirror Descent Inverse Reinforcement Learning

Dong-Sig Han, Hyunseo Kim, Hyundo Lee, Je-Hwan Ryu, Byoung-Tak Zhang

Comments NeurIPS 2022

Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization

Minsu Kim, Junyoung Park, Jinkyoo Park

Comments 23 pages, 8 figures, NeurIPS 2022

Symmetry Teleportation for Accelerated Optimization

Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu

Comments 20 pages, 8 figures, NeurIPS 2022

Is Integer Arithmetic Enough for Deep Learning Training?

Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia

Comments final camera ready submitted to NeurIPS

Invariance-Aware Randomized Smoothing Certificates

Jan Schuchardt, Stephan Günnemann

Comments Accepted at NeurIPS 2022

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Comments NeurIPS 2022

Off-Policy Evaluation in Embedded Spaces

Jaron J. R. Lee, David Arbour, Georgios Theocharous

Comments 9 pages, appeared at NeurIPS 2021 Workshop "Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice", presented virtually Dec 14th 2021

How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents

Yoav Kolumbus, Noam Nisan

Comments This paper was published In Proceeding of NeurIPS 2022

Training Differentially Private Graph Neural Networks with Random Walk Sampling

Morgane Ayle, Jan Schuchardt, Lukas Gosch, Daniel Zügner, Stephan Günnemann

Comments Accepted at the Trustworthy and Socially Responsible Machine Learning Workshop of NeurIPS 2022

Posterior Collapse and Latent Variable Non-identifiability

Yixin Wang, David M. Blei, John P. Cunningham

Comments 19 pages, 4 figures; NeurIPS 2021

Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Benjamin Wilson, William Qi, Tanmay Agarwal, John Lambert, Jagjeet Singh, Siddhesh Khandelwal, Bowen Pan, Ratnesh Kumar, Andrew Hartnett, Jhony Kaesemodel Pontes, Deva Ramanan, Peter Carr, James Hays

Comments Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks

Provably Reliable Large-Scale Sampling from Gaussian Processes

Anthony Stephenson, Robert Allison, Edward Pyzer-Knapp

Comments Main article 4 pages + 14 pages of supplementary material. To be published in NeurIPS 2022 Proceedings Workshop on "Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems"

Product Ranking for Revenue Maximization with Multiple Purchases

Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui

Comments NeurIPS 2022

Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Pierre Chambon, Christian Bluethgen, Curtis P. Langlotz, Akshay Chaudhari

Comments 17 pages, 8 figures

Journal ref Foundation Models for Decision Making Workshop at Neural Information Processing Systems, 2022

An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects

Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong

Comments NeurIPS 2022

Online Training Through Time for Spiking Neural Networks

Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin

Comments Accepted by NeurIPS 2022

Alignment-guided Temporal Attention for Video Action Recognition

Yizhou Zhao, Zhenyang Li, Xun Guo, Yan Lu

Comments Accepted by NeurIPS 2022

Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation

Michael Chang, Thomas L. Griffiths, Sergey Levine

Comments 19 pages, 13 figures, Accepted to the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution

Leon Hetzel, Simon Böhm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian Theis

Comments 10 pages. NeurIPS 2022 conference paper

Projection Robust Wasserstein Distance and Riemannian Optimization

Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan

Comments Accepted by NeurIPS 2020; The first two authors contributed equally; fix the confusing parts in the proof and refine the algorithms and complexity bounds

Multi-modal deep learning system for depression and anxiety detection

Brian Diep, Marija Stanojevic, Jekaterina Novikova

Comments accepted to the PAI4MH workshop at NeurIPS 2022