NeurIPS

Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning

Yuchong Sun, Hongwei Xue, Ruihua Song, Bei Liu, Huan Yang, Jianlong Fu

Comments Accepted by NeurIPS 2022

Factuality Enhanced Language Models for Open-Ended Text Generation

Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale Fung, Mohammad Shoeybi, Bryan Catanzaro

Comments NeurIPS 2022

Semantic Video Segmentation for Intracytoplasmic Sperm Injection Procedures

Chloe He, Raksha Jain, Jérôme Chambost, Céline Jacques, Cristina Hickman

Comments Accepted at the 'Medical Imaging meets NeurIPS Workshop' at the 34th Conference on Neural Information Processing Systems

Honey Authentication with Machine Learning Augmented Bright-Field Microscopy

Chloe He, Alexis Gkantiragas, Gerard Glowacki

Comments Accepted at the 'AI for Social Good' workshop at the 32nd Conference on Neural Information Processing Systems (NeurIPS2018), Montréal, Canada

Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

Anna Willmann, Jurjen Couperus Cabadağ, Yen-Yu Chang, Richard Pausch, Amin Ghaith, Alexander Debus, Arie Irman, Michael Bussmann, Ulrich Schramm, Nico Hoffmann

Comments 7 pages, 5 figures

Journal ref Machine Learning and the Physical Sciences 2022 workshop, NeurIPS

Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models

Zijian Zhang, Zhou Zhao, Zhijie Lin

Comments Accepted by NeurIPS 2022 Conference

Improved Feature Distillation via Projector Ensemble

Yudong Chen, Sen Wang, Jiajun Liu, Xuwei Xu, Frank de Hoog, Zi Huang

Comments NeurIPS 2022

A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking

Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

Comments Accepted by NeurIPS 2022 Dataset and Benchmark Track

SPGP: Structure Prototype Guided Graph Pooling

Sangseon Lee, Dohoon Lee, Yinhua Piao, Sun Kim

Comments 20 pages, 6 figures

Journal ref NeurIPS 2022 Workshop GLFrontiers

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting

Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung

Comments Published at NeurIPS 2022. Camera-ready version

Torsional Diffusion for Molecular Conformer Generation

Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola

Comments NeurIPS 2022

An Analysis of Ensemble Sampling

Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy

Comments [NeurIPS 2022 camera-ready version](https://openreview.net/forum?id=c6ibx0yl-aG) with improved regret bounds

A Preliminary Study on Pattern Reconstruction for Optimal Storage of Wearable Sensor Data

Sazia Mahfuz, Farhana Zulkernine

Comments 6 pages, Learning from Time Series for Health, Workshop at NeurIPS 2022

Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis

Taiki Miyagawa

Comments NeurIPS 2022 (https://openreview.net/forum?id=qq84D17BPu). 1 min & 4 mins short presentation videos are available; feel free to email me :)

Is Out-of-Distribution Detection Learnable?

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

Comments NeurIPS 2022 Outstanding Paper

Transformers from an Optimization Perspective

Yongyi Yang, Zengfeng Huang, David Wipf

Comments This paper was published as a conference paper at NeurIPS 2022

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu

Comments 38 pages; NeurIPS 2022

Models of fairness in federated learning

Kate Donahue, Jon Kleinberg

Comments Preliminary version accepted for oral presentation at Neurips workshop on Learning in Presence of Strategic Behavior (2021) and EAAMO (2022). Final version accepted at The Web Conference (2023)

Learned Robust PCA: A Scalable Deep Unfolding Approach for High-Dimensional Outlier Detection

HanQin Cai, Jialin Liu, Wotao Yin

Comments NeurIPS 2021

Journal ref Advances in Neural Information Processing Systems 34 (2021): 16977-16989

Electrode Clustering and Bandpass Analysis of EEG Data for Gaze Estimation

Ard Kastrati, Martyna Beata Plomecka, Joël Küchler, Nicolas Langer, Roger Wattenhofer

Comments Gaze Meets Machine Learning Workshop (GMML@NeurIPS), New Orleans, Louisiana, USA, December 2022

NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs

Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla

Comments NeurIPS 2022 GLFrontiers

Adaptive Sampling for Probabilistic Forecasting under Distribution Shift

Luca Masserano, Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Youngsuk Park, Michael Bohlke-Schneider

Journal ref Workshop on Distribution Shifts, 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

CalFAT: Calibrated Federated Adversarial Training with Label Skewness

Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu

Comments Accepted to the Conference on the Advances in Neural Information Processing Systems (NeurIPS) 2022

Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Sicheng Zhu, Bang An, Furong Huang

Comments Accepted to NeurIPS 2021. Version 2 includes several content clarifications and image format revisions

When Combinatorial Thompson Sampling meets Approximation Regret

Pierre Perrault

Comments Neurips 2022

Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation

Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang

Comments Accepted to NeurIPS-2022

Sparse, Geometric Autoencoder Models of V1

Jonathan Huml, Abiy Tasissa, Demba Ba

Comments Symmetry and Geometry in Neural Representations (NeurIPS) 2022

Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting

Tian Guo

Comments A causal view on dynamical systems workshop at the 36th Conference on Neural Information Processing Sys- tems (NeurIPS 2022)

PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang, Fazl Barez

Comments The paper has been accepted by The Thirty-ninth International Conference on Machine Learning (ICML 2022) and the Cooperative AI Workshop at 35th Conference on Neural Information Processing Systems (NeurIPS 2021)

What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective

Huan Wang, Suhas Lohit, Mike Jones, Yun Fu

Comments Camera Ready of NeurIPS'22. Code: https://github.com/MingSun-Tse/Good-DA-in-KD