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Bayesian Deep Learning for Partial Differential Equation Parameter
  Discovery with Sparse and Noisy Data

Bayesian Deep Learning for Partial Differential Equation Parameter Discovery with Sparse and Noisy Data

5 August 2021
Christophe Bonneville
Christopher Earls
ArXivPDFHTML

Papers citing "Bayesian Deep Learning for Partial Differential Equation Parameter Discovery with Sparse and Noisy Data"

3 / 3 papers shown
Title
PDE-LEARN: Using Deep Learning to Discover Partial Differential
  Equations from Noisy, Limited Data
PDE-LEARN: Using Deep Learning to Discover Partial Differential Equations from Noisy, Limited Data
R. Stephany
Christopher Earls
16
16
0
09 Dec 2022
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
183
761
0
13 Mar 2020
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,267
0
09 Jun 2012
1