Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology

13 August 2024

Mario De Florio

Zongren Zou

Daniele E. Schiavazzi

George Karniadakis

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Papers citing "Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology"

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Title
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements K. Shukla Zongren Zou Chi Hin Chan Additi Pandey Zhicheng Wang George Karniadakis PINN 81 9 0 30 Jul 2024
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators Gianluca Fabiani Ioannis G. Kevrekidis Constantinos Siettos A. Yannacopoulos 99 13 0 08 Jun 2024
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learning Zongren Zou Tingwei Meng Paula Chen Jérome Darbon George Karniadakis 78 8 0 12 Apr 2024
A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs Dimitrios G. Patsatzis Lucia Russo Constantinos Siettos PINN 64 3 0 18 Mar 2024
A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis John D. Lee Jakob Richter Martin R. Pfaller Jason M. Szafron Karthik Menon ... Michael R. Ma J. Feinstein Jacqueline Kreutzer Alison L. Marsden Daniele E. Schiavazzi AI4CE 26 6 0 01 Dec 2023
Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators Zongren Zou Xuhui Meng George Karniadakis AI4CE 92 24 0 19 Nov 2023
AI-Aristotle: A Physics-Informed framework for Systems Biology Gray-Box Identification Nazanin Ahmadi Daryakenari Mario De Florio K. Shukla George Karniadakis 90 34 0 29 Sep 2023
Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression Zhen Zhang Zongren Zou E. Kuhl George Karniadakis 61 43 0 16 Jul 2023
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 97 39 0 25 Aug 2022
Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems K. Linka Amelie Schäfer Xuhui Meng Zongren Zou George Karniadakis E. Kuhl OOD PINN AI4CE 87 115 0 12 May 2022
Parsimonious Physics-Informed Random Projection Neural Networks for Initial-Value Problems of ODEs and index-1 DAEs Gianluca Fabiani Evangelos Galaris L. Russo Constantinos Siettos 60 29 0 10 Mar 2022
$Physics-informed neural networks for solving Reynolds-averaged Navier$\unicode{x2013}$Stokes equations$ Physics-informed neural networks for solving Reynolds-averaged Navier $\unicode{x2013}$ Stokes equations Hamidreza Eivazi M. Tahani P. Schlatter Ricardo Vinuesa PINN AI4CE 65 267 0 22 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 240 1,164 0 07 Jul 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 100 521 0 09 Feb 2021
Uncertainty Quantification and Deep Ensembles R. Rahaman Alexandre Hoang Thiery UQCV 85 154 0 17 Jul 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 79 212 0 24 Jun 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 243 793 0 13 Mar 2020
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations Vikas Dwivedi Balaji Srinivasan PINN 65 193 0 08 Jul 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 847 5,847 0 05 Dec 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 307 4,817 0 04 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 891 9,364 0 06 Jun 2015
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 153 1,167 0 31 Dec 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 277 2,628 0 29 Jun 2012
MCMC using Hamiltonian dynamics Radford M. Neal 298 3,282 0 09 Jun 2012