Bayesian Model and Dimension Reduction for Uncertainty Propagation: Applications in Random Media

By Constantin Grigo, Phaedon-Stelios Koutsourelakis. 2017

32 citations recorded by the source corpus.

Well-established methods for the solution of stochastic partial differential equations (SPDEs) typically struggle in problems with high-dimensional inputs/outputs. Such difficulties are only amplif...

Subfields: Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Statistics and Probability

Citations in the corpus

• A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime (2019, unknown): “The general framework described above can be effected by a model that integrates the following three key components (see Figure 1 and Grigo and Koutsourelakis (2017, 2019)): • Encoding - Dimension reduction: A mapping from the high-dimensional microstructural description λf to a much…”