NeurIPS

HJ-Gauss: A Monte-Carlo HJ Reachability Scheme

HJ-Gauss: 一种蒙特卡洛HJ可达性方案

Lekan Molu, Venkatraman Renganathan, Namhoon Cho

AI总结 本文提出了一种基于局部PDE线性化的方法，通过冻结系数采样方案解决高维系统中经典网格基HJ求解器内存消耗大的问题，实现了存储和网格无关的算法，适用于高维可达性分析。

Comments NeurIPS 2026 Submission

EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding

脑电（EEG）基础挑战赛：从跨任务到跨主体的脑电解码

Bruno Aristimunha, Dung Truong, Pierre Guetschel, Seyed Yahya Shirazi, Isabelle Guyon, Alexandre R. Franco, Michael P. Milham, Aviv Dotan, Scott Makeig, Alexandre Gramfort, Jean-Remi King, Marie-Constance Corsi, Pedro A. Valdés-Sosa, Amit Majumdar, Alan Evans, Terrence J Sejnowski, Oren Shriki, Sylvain Chevallier, Arnaud Delorme

AI总结 本文介绍一项包含跨任务跨主体脑电解码、精神病理因素预测两项挑战的大规模脑电竞赛，提供对应基线模型，旨在推动泛化性脑电解码模型及相关临床应用的发展。

Comments Approved at Neurips Competition track. webpage: https://eeg2025.github.io/

Journal ref The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2025