Counterfactual Explanations for Machine Learning on Multivariate Time Series Data

25 August 2020

Papers citing "Counterfactual Explanations for Machine Learning on Multivariate Time Series Data"

8 / 8 papers shown

Title
Time Can Invalidate Algorithmic Recourse Giovanni De Toni Stefano Teso Bruno Lepri Andrea Passerini 32 0 0 10 Oct 2024
Explainable AI needs formal notions of explanation correctness Stefan Haufe Rick Wilming Benedict Clark Rustam Zhumagambetov Danny Panknin Ahcène Boubekki XAI 21 0 0 22 Sep 2024
CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models Juan Miguel Lopez Alcaraz Nils Strodthoff DiffM AI4TS CML 29 2 0 24 May 2024
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies Audrey Der Chin-Chia Michael Yeh Yan Zheng Junpeng Wang Zhongfang Zhuang Liang Wang Wei Zhang Eamonn J. Keogh AI4TS 35 2 0 16 Jan 2024
TraCE: Trajectory Counterfactual Explanation Scores Jeffrey N Clark Edward A. Small Nawid Keshtmand Michelle W.L. Wan Elena Fillola Mayoral Enrico Werner Christopher P Bourdeaux Raúl Santos-Rodríguez 20 1 0 27 Sep 2023
Explainable AI for Time Series via Virtual Inspection Layers Johanna Vielhaben Sebastian Lapuschkin G. Montavon Wojciech Samek XAI AI4TS 10 24 0 11 Mar 2023
Learning Certifiably Optimal Rule Lists for Categorical Data E. Angelino Nicholas Larus-Stone Daniel Alabi Margo Seltzer Cynthia Rudin 38 196 0 06 Apr 2017
Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che S. Purushotham Kyunghyun Cho David Sontag Yan Liu AI4TS 197 1,892 0 06 Jun 2016