Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification

12 July 2024

Papers citing "Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification"

9 / 9 papers shown

Title
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series Yihe Wang Yu Han Haishuai Wang Xiang Zhang AI4TS 89 52 0 21 Oct 2023
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency Xiang Zhang Ziyuan Zhao Theodoros Tsiligkaridis Marinka Zitnik AI4TS 132 289 0 17 Jun 2022
The NT-Xent loss upper bound Wilhelm Ågren SSL 28 5 0 06 May 2022
Self-supervised Contrastive Learning for EEG-based Sleep Staging Xue Jiang Jianhui Zhao Bo Du Zhiyong Yuan 90 63 0 16 Sep 2021
Multi-Sample based Contrastive Loss for Top-k Recommendation Hao Tang Guoshuai Zhao Yuxia Wu Xueming Qian 75 33 0 01 Sep 2021
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding S. Tonekaboni Danny Eytan Anna Goldenberg CML SSL AI4TS 157 296 0 01 Jun 2021
Exploring Contrastive Learning in Human Activity Recognition for Healthcare Chi Ian Tang I. Perez-Pozuelo Dimitris Spathis Cecilia Mascolo 91 122 0 23 Nov 2020
Contrastive Representation Learning: A Framework and Review Phúc H. Lê Khắc Graham Healy Alan F. Smeaton SSL AI4TS 317 713 0 10 Oct 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 387 18,866 0 13 Feb 2020