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Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems and optimal experimental design
Presenter
- Omar Ghattas
October 7, 2020
IMSI
Scalable algorithms for optimal experimental design for large-scale Bayesian inverse problems governed by complex models
Presenter
- Omar Ghattas
October 18, 2018
IPAM
Scalable algorithms for optimal training data for Bayesian inference of large scale models
Presenter
- Omar Ghattas
September 27, 2018
IPAM
Scalable methods for optimal control of PDEs with random coefficient fields
Presenter
- Omar Ghattas
May 25, 2017
IPAM
Optimal control of systems governed by PDEs with random parameter fields using quadratic approximations
Presenter
- Omar Ghattas
March 14, 2016
IMA
Panel Session: "Uncertainty in PDEs and optimizations, interations, synergies, challenges" <br>Moderator: <b>Suvrajeet Sen</b> (Ohio State University)
Presenters
- Timothy Barth
- Omar Ghattas
- Alejandro Jofre
- Robert Lipton
- Stephen Robinson
October 20, 2010
IMA
Computing Human to Human Avian Influenza R0 via Transmission Chains and Parameter Estimation
Presenter
- Omar Saucedo
February 9, 2017
MBI
Student Presentation: Deciphering the Gating Properties of P2X4 Receptor Channels using Markov State Models
Presenter
- Omar Khan
August 13, 2014
MBI