Explaining Deep Classification of Time-Series Data with Learned Prototypes

18 April 2019

Papers citing "Explaining Deep Classification of Time-Series Data with Learned Prototypes"

8 / 8 papers shown

Title
Evaluating Simplification Algorithms for Interpretability of Time Series Classification Felix Marti-Perez Brigt Håvardstun Cèsar Ferri Carlos Monserrat Jan Arne Telle AI4TS 26 0 0 13 May 2025
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 95 0 0 14 Sep 2024
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 32 28 0 14 Mar 2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 35 29 0 28 Jan 2023
Intermediate Entity-based Sparse Interpretable Representation Learning Diego Garcia-Olano Yasumasa Onoe Joydeep Ghosh Byron C. Wallace 19 2 0 03 Dec 2022
XAI Methods for Neural Time Series Classification: A Brief Review Ilija vSimić Vedran Sabol Eduardo E. Veas BDL AI4TS 27 13 0 18 Aug 2021
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 19 111 0 29 Nov 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 19 89 0 28 Sep 2020