Doctoral Seminar June 2020

The doctoral seminar was created as a compensation for the retreat, since that could not take place on-site in 2020 and 2021. The annual internal retreat is designed as a platform where doctoral researchers inform each other about their latest research results and open issues. It is a forum for knowledge transfer and information exchange. It follows a Docs-for-Docs concept, where they select content and conference style. The doctoral researchers give presentations on current research topics (both results and open issues).

June 4, 2020

• “Data-based prediction of power system operation and stability” by Johannes Kruse
• “Time-series analysis: Kramers-Moyal and MFDFA in stochastic time series” by Leonardo Rydin Gorjao

June 9, 2020

• “Machine Learning and Bayesian Methods in Neuroscience” by Christian 
• Gerloff
• "BioCatHub: A platform for standardised data acquisition in biocatalysis according to the FAIR data principles" by Stephan Malzacher

June 22, 2020

• “Latent Space Distribution Learning in Energy Systems using Normalizing Flows” by Eike Cramer
• “Bayesian Modelling for Uncertainty Quantification in Metabolic Network Inference” by Fredrik Jadebeck

June 26, 2020

• “Predicting the flow in patient-specific aneurysm geometries using convolutional neural networks” by Viktor Grimm
• “Uncertainty Estimation in Deep Neural Networks” by Felix Terhag