MCNS: Mining Causal Natural Structures Inside Time Series via A Novel Internal Causality Scheme

no code implementations • 13 Sep 2023 • YuanHao Liu, Dehui Du, Zihan Jiang, Anyan Huang, Yiyang Li

To address these challenges, we propose a novel framework called Mining Causal Natural Structure (MCNS), which is automatic and domain-agnostic and helps to find the causal natural structures inside time series via the internal causality scheme.

Causal Inference Time Series +1

Meta Pattern Concern Score: A Novel Evaluation Measure with Human Values for Multi-classifiers

1 code implementation • 14 Sep 2022 • Yanyun Wang, Dehui Du, YuanHao Liu

And a case study shows it can not only find the ideal model reducing 0. 53% of dangerous cases by only sacrificing 0. 04% of training accuracy, but also refine the learning rate to train a new model averagely outperforming the original one with a 1. 62% lower value of itself and 0. 36% fewer number of dangerous cases.

TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack

2 code implementations • 14 Sep 2022 • Yanyun Wang, Dehui Du, Haibo Hu, Zi Liang, YuanHao Liu

Recent years have witnessed the success of recurrent neural network (RNN) models in time series classification (TSC).

Adversarial Attack Time Series +2