Scibib

International Workshop on Machine Learning in Visualisation for Big Data (MLVis), 2020
Explainable Ai Explainability Xaionts

U. Schlegel, D. L. Vo, D. A. Keim D. Seebacher

TS-MULE: Local Interpretable Model-AgnosticExplanations for Time Series Forecast Models

Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI) Workshop, 2021

U. Schlegel, E. Cakmak, H. Arnout M. El-Assady D. Oelke D. A. Keim

Towards Visual Debugging for Multi-Target Time Series Classification

ACM Conference on Intelligent User Interfaces (IUI), 2020

U. Schlegel, D. Oelke, D. A. Keim M. El-Assady

An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks

Pre-registration workshop NeurIPS, 2020

U. Schlegel, W. Jentner, J. Buchmüller E. Cakmak G. Castiglia R. Canepa S. Petralli L. Oneto D. A. Keim D. Anguita

Visual Analytics for Supporting Conflict Resolution in Large Railway Networks

2019 INNS Big Data and Deep Learning (INNSBDDL 2019), 2019

U. Schlegel, H. Arnout, M. El-Assady D. Oelke D. A. Keim

Towards a Rigorous Evaluation of XAI Methods on Time Series

ICCV Workshop on Interpreting and Explaining Visual Artificial Intelligence Models, 2019