On Sampling Spatially-Correlated Random Fields for Complex Geometries

By Simone Pezzuto, Alessio Quaglino, Mark Potse. 2019

13 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geometry and Topology, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Paris Perdikaris
2. Yibo Yang

In Geometry and Topology

1. Paris Perdikaris
2. Yibo Yang

In Statistics and Probability

1. Yibo Yang
2. Ellen Kuhl
3. Paris Perdikaris
4. F. Sahli Costabal
5. Daniel E. Hurtado
6. G. Em Karniadakis
7. Sifan Wang
8. Jian-Xun Wang

Citations in the corpus

• Physics-Informed Neural Networks for Cardiac Activation Mapping (2020, methodology): “Second, our uncertainty estimates are only approximations, since the true uncertainties depend on the geodesic distance between points on the manifold and not on the Euclidean distance in R 3 , which we have used to parametrize this problem [3, 42].”