Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems

12 May 2022

Papers citing "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems"

37 / 37 papers shown

Title
Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles P. Flores Olga Graf P. Protopapas K. Pichara PINN 28 0 0 09 May 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 76 0 0 25 Apr 2025
Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries Ali Kashefi T. Mukerji 3DPC PINN 47 0 0 08 Apr 2025
Online Traffic Density Estimation using Physics-Informed Neural Networks Dennis Wilkman Kateryna Morozovska Karl H. Johansson Matthieu Barreau 31 0 0 04 Apr 2025
Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble Zongren Zou Zhicheng Wang George Karniadakis PINN AI4CE 65 2 0 08 Mar 2025
MILP initialization for solving parabolic PDEs with PINNs Sirui Li Federica Bragone Matthieu Barreau Kateryna Morozovska 33 0 0 28 Jan 2025
Physics-informed deep learning for infectious disease forecasting Y. Qian Éric Marty Avranil Basu Avranil Basu Eamon B. O'Dea Xianqiao Wang Spencer Fox Pejman Rohani John M. Drake He Li PINN AI4CE 78 2 0 16 Jan 2025
Empowering Bayesian Neural Networks with Functional Priors through Anchored Ensembling for Mechanics Surrogate Modeling Applications Javad Ghorbanian Nicholas Casaprima Audrey Olivier 28 0 0 08 Sep 2024
HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment Inass Soukarieh Gerhard Hessler Hervé Minoux Marcel Mohr Friedemann Schmidt Jan Wenzel Pierre Barbillon Hugo Gangloff Pierre Gloaguen 24 0 0 26 Aug 2024
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology Mario De Florio Zongren Zou Daniele E. Schiavazzi George Karniadakis 26 3 0 13 Aug 2024
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 42 7 0 30 Jul 2024
Accounting for plasticity: An extension of inelastic Constitutive Artificial Neural Networks Birte Boes Jaan-Willem Simon H. Holthusen AI4CE 32 6 0 27 Jul 2024
Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation Yifei Zong D. Barajas-Solano A. Tartakovsky 36 1 0 05 Jul 2024
WANCO: Weak Adversarial Networks for Constrained Optimization problems Gang Bao Dong Wang Boyi Zou 39 1 0 04 Jul 2024
Initialization-enhanced Physics-Informed Neural Network with Domain Decomposition (IDPINN) Chenhao Si Ming Yan AI4CE PINN 33 3 0 05 Jun 2024
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks K. Shukla Juan Diego Toscano Zhicheng Wang Zongren Zou George Karniadakis 24 73 0 05 Jun 2024
Integrating GNN and Neural ODEs for Estimating Two-Body Interactions in Mixed-Species Collective Motion Masahito Uwamichi S. Schnyder Tetsuya J. Kobayashi Satoshi Sawai 15 0 0 26 May 2024
Large scale scattering using fast solvers based on neural operators Zongren Zou Adar Kahana Enrui Zhang Eli Turkel Rishikesh Ranade Jay Pathak George Karniadakis 34 1 0 20 May 2024
Variational Bayesian surrogate modelling with application to robust design optimisation Thomas A. Archbold Ieva Kazlauskaite F. Cirak 20 1 0 23 Apr 2024
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learning Zongren Zou Tingwei Meng Paula Chen Jérome Darbon George Karniadakis 36 7 0 12 Apr 2024
A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty Pratyush Kumar Singh Kathryn A. Farrell-Maupin D. Faghihi 32 6 0 13 Mar 2024
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 31 0 0 23 Jan 2024
Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators Zongren Zou Xuhui Meng George Karniadakis AI4CE 25 19 0 19 Nov 2023
Correcting model misspecification in physics-informed neural networks (PINNs) Zongren Zou Xuhui Meng George Karniadakis PINN 24 41 0 16 Oct 2023
A physics and data co-driven surrogate modeling method for high-dimensional rare event simulation Jianhua Xian Ziqi Wang AI4CE 20 9 0 30 Sep 2023
Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution S. Pérez P. Poncet 25 3 0 24 Aug 2023
Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression Zhen Zhang Zongren Zou E. Kuhl George Karniadakis 21 41 0 16 Jul 2023
LatentPINNs: Generative physics-informed neural networks via a latent representation learning M. H. Taufik T. Alkhalifah AI4CE DiffM 41 4 0 11 May 2023
A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes Minglang Yin Zongren Zou Enrui Zhang C. Cavinato J. Humphrey George Karniadakis SyDa MedIm AI4CE 45 11 0 04 May 2023
Physics-informed radial basis network (PIRBN): A local approximating neural network for solving nonlinear PDEs Jinshuai Bai Guirong Liu Ashish Gupta Laith Alzubaidi Xinzhu Feng Yuantong T. Gu PINN 16 1 0 13 Apr 2023
Physics-informed PointNet: On how many irregular geometries can it solve an inverse problem simultaneously? Application to linear elasticity Ali Kashefi Leonidas J. Guibas T. Mukerji PINN 3DPC AI4CE 24 9 0 22 Mar 2023
Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks Shuai Han Lukas Stelz Horst Stoecker L. Wang Kai Zhou AI4CE PINN 16 9 0 17 Feb 2023
L-HYDRA: Multi-Head Physics-Informed Neural Networks Zongren Zou George Karniadakis AI4CE 16 26 0 05 Jan 2023
Utilising physics-guided deep learning to overcome data scarcity Jinshuai Bai Laith Alzubaidi Qingxia Wang E. Kuhl Bennamoun Yuantong T. Gu PINN AI4CE 22 3 0 24 Nov 2022
A new family of Constitutive Artificial Neural Networks towards automated model discovery K. Linka E. Kuhl AI4CE 23 156 0 15 Sep 2022
MRF-PINN: A Multi-Receptive-Field convolutional physics-informed neural network for solving partial differential equations Shihong Zhang Chi Zhang Bo Wang AI4CE 13 3 0 06 Sep 2022
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 170 756 0 13 Mar 2020