270 citations · 1.5k across the 27 of their papers we have counts for
4 papers · 1 filter
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…
Non-intrusive reduced-order models for parametric partial differential equations via data-driven operator inference
Shane A McQuarrie, Parisa Khodabakhshi, Karen E Willcox
This work formulates a new approach to reduced modeling of parameterized, time-dependent partial differential equations (PDEs). The method employs Operator Inference, a scientific…
Reduced operator inference for nonlinear partial differential equations
Elizabeth Qian, Ionut-Gabriel Farcas, Karen Willcox
We present a new scientific machine learning method that learns from data a computationally inexpensive surrogate model for predicting the evolution of a system governed by a time-…
Certifiable Risk-Based Engineering Design Optimization
Anirban Chaudhuri, Boris Kramer, Matthew Norton +2
Reliable, risk-averse design of complex engineering systems with optimized performance requires dealing with uncertainties. A conventional approach is to add safety margins to a de…