Physic Informed Neural Network

March 15, 2023

On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem
Yu Yang, Helin Gong, Qihong Yang, Yangtao Deng, Qiaolin He, Shiquan Zhang
Loss Function Physic Informed Neural Network Uncertainty Estimation Nuclear Reactor Noise Prior Eigenvalue Problem Neutron Diffusion

March 13, 2023

Improving physics-informed neural networks with meta-learned optimization
Alex Bihlo
Physic Informed Neural Network Meta Learned
Topology optimization with physics-informed neural networks: application to noninvasive detection of hidden geometries
Saviz Mowlavi, Ken Kamrin
Application Proficiency Data Detection Physic Informed Neural Network Topology Optimization Complex Geometry Geometric Optimization Topological Prior Topology Generation
Symbolic Regression for PDEs using Pruned Differentiable Programs
Ritam Majumdar, Vishal Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana
Physic Informed Neural Network Symbolic Regression Navier Stokes Deep Learning Solution Differentiable Program

March 9, 2023

CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems
N. V. Jagtap, M. K. Mudunuru, K. B. Nakshatrala
Physic Informed Neural Network Reg PINNs Thermal Control Spatial Cooling

March 6, 2023

An Analysis of Physics-Informed Neural Networks
Edward Small
Neural Network General Analysis Physic Informed Neural Network Optimisation Problem Seismic Image

March 3, 2023

March 2, 2023

Physics-informed neural networks for solving forward and inverse problems in complex beam systems
Taniya Kapoor, Hongrui Wang, Alfredo Nunez, Rolf Dollevoet
Loss Function Physic Informed Neural Network Inverse Problem Euler Bernoulli Beam Beam System

February 28, 2023

A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions
Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
Physic Informed Neural Network Unifying Framework PINN Method Time Dependent Partial Differential Equation Temporal Decomposition Domain Decomposition Method

February 26, 2023

Efficient physics-informed neural networks using hash encoding
Xinquan Huang, Tariq Alkhalifah
High Efficiency Physic Informed Neural Network Numerical Method Finite Difference Hash Code Hash Encoding Robust Risk

February 25, 2023

February 23, 2023

Solving differential equations using physics informed deep learning: a hand-on tutorial with benchmark tests
Hubert Baty, Leo Baty
Neural Network Deep Learning Physic Informed Neural Network Differential Equation Tutorial Review Theoretical Physic Ordinary Differential Equation High Quality Benchmark

February 20, 2023

Non-rigid Medical Image Registration using Physics-informed Neural Networks
Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed, Mark Emberton, Dean C. Barratt, Zeike A. Taylor, Yipeng Hu
Physic Informed Neural Network Medical Image Registration Prostate Age Gap Biomechanical Model Ultrasound Registration

February 19, 2023

Physics-aware deep learning framework for linear elasticity
Arunabha M. Roy, Rikhi Bose
Physic Informed Neural Network Deep Learning Framework Physic Informed Robust Deep Robust Neural Network Nonlinear Elasticity

February 17, 2023

February 16, 2023

The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach
Yongcun Song, Xiaoming Yuan, Hangrui Yue
Optimization Purpose Physic Informed Neural Network Deep Learning Approach Nonsmooth Dynamical System

February 15, 2023

On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it
Andrea Bonfanti, Roberto Santana, Marco Ellero, Babak Gholami
Neural Network Strong Generalization Physic Informed Neural Network Related Hyperparameters Domain Decomposition Training Domain PINN Model Consistent Prediction

Physic Informed Neural Network

Papers

On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem

Improving physics-informed neural networks with meta-learned optimization

Topology optimization with physics-informed neural networks: application to noninvasive detection of hidden geometries

Symbolic Regression for PDEs using Pruned Differentiable Programs

CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems

An Analysis of Physics-Informed Neural Networks

NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training

Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks

Physics-informed neural networks for solving forward and inverse problems in complex beam systems

A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions

Efficient physics-informed neural networks using hash encoding

Achieving High Accuracy with PINNs via Energy Natural Gradients

Ensemble learning for Physics Informed Neural Networks: a Gradient Boosting approach

Solving differential equations using physics informed deep learning: a hand-on tutorial with benchmark tests

Non-rigid Medical Image Registration using Physics-informed Neural Networks

Physics-aware deep learning framework for linear elasticity

h-analysis and data-parallel physics-informed neural networks

Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks

The ADMM-PINNs Algorithmic Framework for Nonsmooth PDE-Constrained Optimization: A Deep Learning Approach

On the Generalization of PINNs outside the training domain and the Hyperparameters influencing it