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stat.CO2021
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion
Han Lu, Mohammad Khalil, Thomas Catanach +5
In the context of Bayesian inversion for scientific and engineering modeling, Markov chain Monte Carlo sampling strategies are the benchmark due to their flexibility and robustness…
cs.LG2021
Mesh-based graph convolutional neural networks for modeling materials with microstructure
Ari Frankel, Cosmin Safta, Coleman Alleman +1
Predicting the evolution of a representative sample of a material with microstructure is a fundamental problem in homogenization. In this work we propose a graph convolutional neur…