56 citations · 64 across the 4 of their papers we have counts for
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cs.LG2023★ 5 cited
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution
Sarah Perez, Philippe Poncet
In this article, we present a novel data assimilation strategy in pore-scale imaging and demonstrate that this makes it possible to robustly address reactive inverse problems incor…
physics.comp-ph2023★ 56 cited
Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems
Sarah Perez, Suryanarayana Maddu, Ivo F. Sbalzarini +1
In this paper, we present a novel methodology for automatic adaptive weighting of Bayesian Physics-Informed Neural Networks (BPINNs), and we demonstrate that this makes it possible…