Keynote by Kai Puolamäki - Explainable and Robust Scientific Machine Learning: Applications in Modelling Molecular Atmospheric Transformations
9:50–10:30
Oral Presentations: - Counterfactual Explanations for Time Series Should be Human-Centered and Temporally Coherent in Interventions - Emmanuel Chukwu (Eindhoven University of Technology)
- InfoClus: Informative Clustering of High-dimensional Data Embeddings - Fuyin Lai (Ghent University)
Coffee break 10:30–10:50
10:50–11:40
Keynote by Yvan Saeys - Towards trustworthy and explorable embeddings of single-cell omics data
11:40-12:00
Oral Presentation - Trustworthiness and Medical Usefulness of Explainability Techniques in ML-Supported Depression Screening within Primary Care - Alejandro Kuratomi (Stockholm University)
12:00–12:30
Poster session
Location: room Poente 0 (the common room for all workshop posters) - Trustworthiness and Medical Usefulness of Explainability Techniques in ML-Supported Depression Screening within Primary Care - Counterfactual Explanations for Time Series Should be Human-Centered and Temporally Coherent in Interventions - Interpretable Sample Selection with Exceptional Model Mining - InfoClus: Informative Clustering of High-dimensional Data Embeddings