activity
20132023
most citedScalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

171 citations · 898 across the 46 of their papers we have counts for

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cs.LG2021★ 30 cited

Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks

Thomas O'Leary-Roseberry, Xiaosong Du, Anirban Chaudhuri +3

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs a…

cs.LG2020★ 19 cited

Projected Stein Variational Gradient Descent

Peng Chen, Omar Ghattas

The curse of dimensionality is a longstanding challenge in Bayesian inference in high dimensions. In this work, we propose a projected Stein variational gradient descent (pSVGD) me…