NeurIPS

Wavelets Beat Monkeys at Adversarial Robustness

Jingtong Su, Julia Kempe

Comments Machine Learning and the Physical Sciences Workshop, NeurIPS 2022

Fast Vision Transformers with HiLo Attention

Zizheng Pan, Jianfei Cai, Bohan Zhuang

Comments NeurIPS 2022 camera ready

Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning

Dingwen Kong, Lin F. Yang

Comments 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

Faster Deep Reinforcement Learning with Slower Online Network

Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola

Comments Published at the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022)

Matérn Gaussian processes on Riemannian manifolds

Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth

Journal ref Advances in Neural Information Processing Systems, 2020

Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation

Josh Gardner, Zoran Popović, Ludwig Schmidt

Comments To appear at Neural Information Processing Systems (NeurIPS) 2022. Code at https://github.com/jpgard/subgroup-robustness-grows-on-trees

Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers

Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls

Comments NeurIPS 2022

Variational Diffusion Models

Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho

Comments Published at NeurIPS'21

Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang

Comments Published on NeurIPS 2021, 24 pages, 10 figures

Measuring Reliability of Large Language Models through Semantic Consistency

Harsh Raj, Domenic Rosati, Subhabrata Majumdar

Comments NeurIPS 2022 ML Safety Workshop, https://neurips2022.mlsafety.org

Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering

Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang

Comments Accepted by NeurIPS 2022

Improving Certified Robustness via Statistical Learning with Logical Reasoning

Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li

Comments Accepted by 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

OpenAL: Evaluation and Interpretation of Active Learning Strategies

W. Jonas, A. Abraham, L. Dreyfus-Schmidt

Comments Published in NeurIPS 2022 Workshop on Human in the Loop Learning, 8 pages

A Novel Two-level Causal Inference Framework for On-road Vehicle Quality Issues Diagnosis

Qian Wang, Huanyi Shui, Thi Tu Trinh Tran, Milad Zafar Nezhad, Devesh Upadhyay, Kamran Paynabar, Anqi He

Comments Accepted by NeurIPS 2022 Workshop on Causal Machine Learning for Real-World Impact (CML4Impact 2022)

Prophet Attention: Predicting Attention with Future Attention for Image Captioning

Fenglin Liu, Xuancheng Ren, Xian Wu, Wei Fan, Yuexian Zou, Xu Sun

Comments Accepted by NeurIPS 2020

Transformer Utilization in Medical Image Segmentation Networks

Saikat Roy, Gregor Koehler, Michael Baumgartner, Constantin Ulrich, Jens Petersen, Fabian Isensee, Klaus Maier-Hein

Comments Accepted in NeurIPS 2022 workshop, Medical Imaging Meets NeurIPS (MedNeurIPS)

ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model

Rao Fu, Xiao Zhan, Yiwen Chen, Daniel Ritchie, Srinath Sridhar

Comments Presented at the Advances in Neural Information Processing Systems (NeurIPS) 2022

Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne

Comments 38 pages, 6 figures

Journal ref NeurIPS 35, 16533--16547 (2022)

Plug & Play Directed Evolution of Proteins with Gradient-based Discrete MCMC

Patrick Emami, Aidan Perreault, Jeffrey Law, David Biagioni, Peter C. St. John

Comments 31 pages, 8 figures. To appear in the Machine Learning: Science & Technology (ML:S&T) journal. Code is available at https://github.com/pemami4911/ppde. A short version of this work appeared at the NeurIPS 2022 Machine Learning in Structural Biology Workshop

Coordinate Linear Variance Reduction for Generalized Linear Programming

Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas

Comments 39 pages, NeurIPS 2022

Private Estimation with Public Data

Alex Bie, Gautam Kamath, Vikrant Singhal

Comments 55 pages; updated funding acknowledgement + simulation results from NeurIPS 2022 camera-ready

A Policy-Guided Imitation Approach for Offline Reinforcement Learning

Haoran Xu, Li Jiang, Jianxiong Li, Xianyuan Zhan

Comments Oral @ NeurIPS 2022; An extended version with more experiments & correct some experiment details in previous version

Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection

Yiming Li, Yang Bai, Yong Jiang, Yong Yang, Shu-Tao Xia, Bo Li

Comments This work is accepted by the NeurIPS 2022 (Oral, TOP 2%). The first two authors contributed equally to this work. 25 pages. We have fixed some typos in the previous version

Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling

Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet

Comments NeurIPS 2021 (spotlight)

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias

Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

Journal ref 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

When Does Re-initialization Work?

Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu

Comments Published in PMLR Volume 187; spotlight presentation at I Can't Believe It's Not Better Workshop at NeurIPS 2022

Optimal Algorithms for Decentralized Stochastic Variational Inequalities

Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander Gasnikov

Comments Appears in: Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Minor modifications with respect to the NeurIPS version. 58 pages, 6 algorithms, 9 figures, 4 tables

Journal ref https://proceedings.neurips.cc/paper_files/paper/2022/hash/c959bb2cb164d37569a17fa67494d69a-Abstract-Conference.html

Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees

Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander Gasnikov

Comments Appears in: Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Minor modifications with respect to the NeurIPS version. 73 pages, 9 algorithms, 2 figures, 2 tables

Journal ref https://proceedings.neurips.cc/paper_files/paper/2022/hash/5ac1428c23b5da5e66d029646ea3206d-Abstract-Conference.html

Decentralized Local Stochastic Extra-Gradient for Variational Inequalities

Aleksandr Beznosikov, Pavel Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U Stich, Alexander Gasnikov

Comments Appears in: Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Minor modifications with respect to the NeurIPS version. 43 pages, 1 algorithm, 6 figures, 2 tables

Journal ref https://proceedings.neurips.cc/paper_files/paper/2022/hash/f9379afacdbabfdc6b060972b60f9ab8-Abstract-Conference.html

TAP-Vid: A Benchmark for Tracking Any Point in a Video

Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang

Comments Published in NeurIPS Datasets and Benchmarks track, 2022