ELLIS Health Workshop: Explainable Machine Learning & Biological Mechanisms
16 December 2020 Workshop Online
16 December 2020
The ELLIS Health program of the European Laboratory for Learning and Intelligent Systems (ELLIS) organizes a series of online workshops in the wider area of machine learning and health. These workshop bring together external guest speakers with contributions from trainees from organising labs. The ELLIS Health Workshop on Explainable Machine Learning & Biological Mechanisms took place on 16 December 2020. It focused on efforts to make machine learning interpretable and useful for understanding biology and advancing therapy.
Target audience:
- Machine learning researchers interested in applications biology and medicine
- Biologists and bioinformaticians who want to expand their knowledge and toolbox of machine learning methods
Organizers:
- Christoph Bock (CeMM Vienna & Medical University of Vienna)
- Oliver Stegle (DKFZ Heidelberg & EMBL Heidelberg)
Program and recorded talk videos:
- Introduction & Welcome - Oliver Stegle (DKFZ & EMBL Heidelberg)
- Invariances, Causality, and Stable Prediction - Jonas Peters (University of Copenhagen)
- Learning Representations of Chemical Structures and their Interpretability - Regina Barzilay (MIT)
- Interpretable deep learning models of cells DCell and DrugCell - Trey Ideker (University of California San Diego)
- Probabilistic factor models for an interpretable integration of multi-modal comics data - Britta Velten (DFKZ Heidelberg)
- Knowledge-primed neural networks: Deep Learning on biological networks - Nikolaus Fortelny (CeMM Vienna & University of Salzburg)
- Wrap-up & Summary - Christoph Bock (CeMM Vienna)
