Based on our Stan activation function proposed in our paper: https://t.co/dhAFQaUQyh
@nvidia has implemented and documented the conclusion: Stan activation yields faster convergence and better validation accuracy.
https://t.co/g5T0G5GByc
Based on our Stan activation function proposed in our paper: https://t.co/dhAFQaUQyh
@nvidia has implemented and documented the conclusion: Stan activation yields faster convergence and better validation accuracy.
https://t.co/g5T0G5GByc
Transformers in Time Series: A Survey
A curated list of awesome resources (papers, code, data) on Transformers in Time Series categorized by tasks, including:
• Forecasting
• Anomaly detection
• Classification
Transformers capture long-range dependencies and interactions.
"Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee", by Bo Shen, Weijun Xie, Zhenyu (James) Kong. https://t.co/uHEp5Lfu37
Our recent paper with @xwj06 and @zhenyukong on "Smooth Robust Tensor Completion for Background/Foreground Separation with Missing Pixels: Novel Algorithm with Convergence Guarantee" is published in the Journal of Machine Learning Research
https://t.co/pQ8PaDgVDi
All four SMART lab teams won first place in their best paper competitions at the #IISEAnnual2022
So proud to be coauthors for all these four papers! Thank you @IISEMD and @qcreiise for all the efforts!
Very happy to be a part of the VT SMART lab (https://t.co/h3T3i2b6K8) led by Dr. @zhenyukong. This year VT SMART lab has finalists for four Best Paper Competitions @qcreiise@IISEMD in the upcoming @iisenet.
Very happy to be a part of the VT SMART lab (https://t.co/h3T3i2b6K8) led by Dr. @zhenyukong. This year VT SMART lab has finalists for four Best Paper Competitions @qcreiise@IISEMD in the upcoming @iisenet.