Machine Learning for Fluid Mechanics - Petros Koumoutsakos,
at
EECS Colloquium, UC Berkeley, USA,
Wednesday, October 30, 2019
Presentations
Machine Learning for Fluid Mechanics - Petros Koumoutsakos,
at
Los Angeles, USA,
Monday, October 28, 2019
Recurrent neural networks for spatiotemporal prediction of chaotic dynamics - Pantelis Vlachas,
at
DMOFM 2019, Karlsruhe, Germany,
Wednesday, October 2, 2019:
Hierarchical Bayesian Uncertainty Quantification for a Red Blood Cell Model - George Arampatzis,
at
UNCECOMP 2019, Crete, Greece,
Monday, June 24, 2019:
A High Performance Computing Framework
for Multiphase, Turbulent Flows
on Structured Grids - Petr Karnakov,
at
PASC 2019, Zurich, Switzerland,
Friday, June 14, 2019:
CCMA-ES for constrained optimization - Daniel Waelchli,
at
PASC 2019, Zurich, Switzerland,
Wednesday, June 12, 2019:
Remember and Forget for Experience Replay - Guido Novati,
at
ICML 2019, Los Angeles, USA,
Wednesday, June 12, 2019:
Data as Models: Bayesian Inference for Molecular Simulations - Petros Koumoutsakos,
at
CECAM Workshop 2019, Lausanne, Switzerland,
Thursday, May 23, 2019
Coalescence and transport of bubbles and drops - Petr Karnakov,
at
ICMF 2019, Rio-de-Janeiro, Brazil,
Monday, May 20, 2019:
High Performance Computing and Data science interfaces to predict, control and understand Fluid Mechanics - Petros Koumoutsakos,
at
IPAM Workshop III: “HPC for Computationally and Data-Intensive Problems", Los Angeles, USA,
Thursday, November 8, 2018