Zum Inhalt springen
Technische Universität München

News

New work on "A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime"

More details here

Our group will participate in this year's SIAM CSE 2019 conference with 5 papers

More details here

New work on "Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data"

More details here

Talk on "Data-driven, physics-aware, coarse-grained models"

at the Seminar on Numerical Analysis and Applied Mathematics at KU Leuven

The paper "Predictive Collective Variable Discovery with Deep Bayesian Models" has been accepted for publication.

More details here

Keynote talk on "Physics-aware, coarse-grained models for high-dimensional, uncertainty quantification"

at the "Big Data Challenges for Predictive Modeling of Complex Systems" Workshop at the University of Hong Kong

Talk on "Coarse-grained variable and model discovery through latent variables and neural nets"

at the CECAM Workshop on "New frontiers in particle-based multiscale and coarse-grained modeling"

The paper "Physics-constrained, data-driven discovery of coarse-grained dynamics" has been accepted for publication.

More details here

The paper "Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography" has been accepted for publication

Mode details here

Our group will participate in WCCM 2018 with 3 papers

More details here

To top