Conferences - Seminars
Big data and uncertainty quantification: statistical inference and information-theoretic techniques applied to computational chemistry
By Carsten Hartmann, BTU Cottbus-Senftenberg Fabio Nobile, EPFL Frank Pinski, University of Cincinnati Tim Sullivan, Zuse Institute Berlin
An incentive to use coarse-grained models is to use them for inference and control instead of the original (often intractable) model. Since coarse-grained models are always “wrong”, questions such as inference under model misspecification or goal-oriented uncertainty quantification (e.g. for control) come into play. This workshop will address such topics, with a special focus on predictive modelling, uncertainty quantification in molecular simulation and sensitivity analysis.
26 to 29 March 2019 - CIB premises (Room GA 3 21).
1 to 3 April 2019 - CECAM premises (Room BCH 3113).
Part of the Semester : Multi-scale Mathematical Modelling and Coarse-grain Computational Chemistry
Organization John Maddocks, EPFL - Christof Schütte, Freie Universität Berlin - Carsten Hartmann, BTU Cottbus-Senftenberg
Accessibility General public