107 citations · 108 across the 3 of their papers we have counts for
3 papers
Hybridizing Physical and Data-driven Prediction Methods for Physicochemical Properties
Fabian Jirasek, Robert Bamler, Stephan Mandt
We present a generic way to hybridize physical and data-driven methods for predicting physicochemical properties. The approach `distills' the physical method's predictions into a p…
Attribute-based Explanations of Non-Linear Embeddings of High-Dimensional Data
Jan-Tobias Sohns, Michaela Schmitt, Fabian Jirasek +2
Embeddings of high-dimensional data are widely used to explore data, to verify analysis results, and to communicate information. Their explanation, in particular with respect to th…
Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion
Fabian Jirasek, Rodrigo A. S. Alves, Julie Damay +6
Activity coefficients, which are a measure of the non-ideality of liquid mixtures, are a key property in chemical engineering with relevance to modeling chemical and phase equilibr…