Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes

17 February 2024

Papers citing "Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes"

5 / 5 papers shown

Title
Deep learning and multi-level featurization of graph representations of microstructural data Reese E. Jones C. Safta A. Frankel AI4CE 38 4 0 29 Sep 2022
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter Ruben Villarreal Nikolaos N. Vlassis Nhon N. Phan Tommie A. Catanach Reese E. Jones N. Trask S. Kramer WaiChing Sun OffRL 27 11 0 27 Sep 2022
Projected Stein Variational Gradient Descent Peng Chen Omar Ghattas BDL 50 68 0 09 Feb 2020
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 230 7,903 0 13 Jun 2015
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 175 2,577 0 28 Mar 2008