Physics-Informed Neural Network (PINN) Evolution and Beyond: A Systematic Literature Review and Bibliometric Analysis

DSFA-PINN: Deep Spectral Feature Aggregation Physics Informed Neural Network

(2022) Muhammad Rafiq et al.   IEEE Access

Controlling Chaos in Van Der Pol Dynamics Using Signal-Encoded Deep Learning

(2022) Hanfeng Zhai et al.   Mathematics

Deep Learning (CNN, RNN) Applications for Smart Homes: A Systematic Review

(2022) Jiyeon Yu et al.   Computers

GW-PINN: A deep learning algorithm for solving groundwater flow equations

(2022) Xiaoping Zhang et al.   ADVANCES IN WATER RESOURCES

Multi-output physics-informed neural networks for forward and inverse PDE problems with uncertainties

(2022) Mingyuan Yang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Physics informed neural networks for continuum micromechanics

(2022) Alexander Henkes et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method

(2022) Pao-Hsiung Chiu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Physics-informed neural networks for the shallow-water equations on the sphere

(2022) Alex Bihlo et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A novel meta-learning initialization method for physics-informed neural networks

(2022) Xu Liu et al.   NEURAL COMPUTING & APPLICATIONS

Graph-Informed Neural Networks for Regressions on Graph-Structured Data

(2022) Stefano Berrone et al.   Mathematics

A Deep Neural Network Approach to Solving for Seal’s Type Partial Integro-Differential Equation

(2022) Bihao Su et al.   Mathematics

Deep Q-Learning Based Reinforcement Learning Approach for Network Intrusion Detection

(2022) Hooman Alavizadeh et al.   Computers

A non-intrusive neural network model order reduction algorithm for parameterized parabolic PDEs

(2022) Tao Zhang et al.   COMPUTERS & MATHEMATICS WITH APPLICATIONS

Developing a physics-informed and physics-penalized neural network model for preliminary design of multi-stage friction pendulum bearings

(2022) Ahed Habib et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Physics-informed Karhunen-Loéve and neural network approximations for solving inverse differential equation problems

(2022) Jing Li et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Self-adaptive loss balanced Physics-informed neural networks

(2022) Zixue Xiang et al.   NEUROCOMPUTING

A pretraining domain decomposition method using artificial neural networks to solve elliptic PDE boundary value problems

(2022) Jeong-Kweon Seo   Scientific Reports

End-to-End Training of Deep Neural Networks in the Fourier Domain

(2022) András Fülöp et al.   Mathematics

DWNN: Deep Wavelet Neural Network for Solving Partial Differential Equations

(2022) Ying Li et al.   Mathematics

ModalPINN: An extension of physics-informed Neural Networks with enforced truncated Fourier decomposition for periodic flow reconstruction using a limited number of imperfect sensors

(2022) Gaétan Raynaud et al.   JOURNAL OF COMPUTATIONAL PHYSICS

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

(2022) Zheyuan Hu et al.   SIAM JOURNAL ON SCIENTIFIC COMPUTING

Error analysis for physics-informed neural networks (PINNs) approximating Kolmogorov PDEs

(2022) Tim De Ryck et al.   ADVANCES IN COMPUTATIONAL MATHEMATICS

Applications of Physics-Informed Neural Networks in Power Systems - A Review

(2022) Bin Huang et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Forecasting of the Prevalence of Dementia Using the LSTM Neural Network in Taiwan

(2021) Stephanie Yang et al.   Mathematics

A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications

(2021) Navid Zobeiry et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Physics-Informed Neural Networks for Heat Transfer Problems

(2021) Shengze Cai et al.   JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME

Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems

(2021) Andrea D’Ambrosio et al.   Mathematics

A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

(2021) Ehsan Haghighat et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A physics-guided neural network framework for elastic plates: Comparison of governing equations-based and energy-based approaches

(2021) Wei Li et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs

(2021) Siddhartha Mishra et al.   IMA JOURNAL OF NUMERICAL ANALYSIS

Multi-fidelity Bayesian neural networks: Algorithms and applications

(2021) Xuhui Meng et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Physics-Informed Deep Learning for Computational Elastodynamics without Labeled Data

(2021) Chengping Rao et al.   JOURNAL OF ENGINEERING MECHANICS

Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics

(2021) Weiqi Ji et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Data-driven femtosecond optical soliton excitations and parameters discovery of the high-order NLSE using the PINN

(2021) Yin Fang et al.   NONLINEAR DYNAMICS

Uncovering near-wall blood flow from sparse data with physics-informed neural networks

(2021) Amirhossein Arzani et al.   PHYSICS OF FLUIDS

Physics-Informed Neural Networks and Functional Interpolation for Data-Driven Parameters Discovery of Epidemiological Compartmental Models

(2021) Enrico Schiassi et al.   Mathematics

Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture

(2021) Sina Amini Niaki et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Local extreme learning machines and domain decomposition for solving linear and nonlinear partial differential equations

(2021) Suchuan Dong et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

TONR: An exploration for a novel way combining neural network with topology optimization

(2021) Zeyu Zhang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Parallel physics-informed neural networks via domain decomposition

(2021) Khemraj Shukla et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Physics-informed machine learning for reduced-order modeling of nonlinear problems

(2021) Wenqian Chen et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Physics-informed meta learning for machining tool wear prediction

(2021) Yilin Li et al.   JOURNAL OF MANUFACTURING SYSTEMS

Physics-informed learning of governing equations from scarce data

(2021) Zhao Chen et al.   Nature Communications

Deep Learning Approach to Mechanical Property Prediction of Single-Network Hydrogel

(2021) Jing-Ang Zhu et al.   Mathematics

Discovering a universal variable-order fractional model for turbulent Couette flow using a physics-informed neural network

(2020) Pavan Pranjivan Mehta et al.   Fractional Calculus and Applied Analysis

Physics-Informed Neural Networks for Cardiac Activation Mapping

(2020) Francisco Sahli Costabal et al.   Frontiers in Physics

Physics-informed neural networks for missing physics estimation in cumulative damage models: a case study in corrosion fatigue

(2020) Arinan Dourado et al.   JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING

Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems

(2020) Ameya D. Jagtap et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

nPINNs: Nonlocal physics-informed neural networks for a parametrized nonlocal universal Laplacian operator. Algorithms and applications

(2020) G. Pang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Adaptive fourth-order phase field analysis using deep energy minimization

(2020) Somdatta Goswami et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

PPINN: Parareal physics-informed neural network for time-dependent PDEs

(2020) Xuhui Meng et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Solving Partial Differential Equations Using Deep Learning and Physical Constraints

(2020) Yanan Guo et al.   Applied Sciences-Basel

A generic physics-informed neural network-based constitutive model for soft biological tissues

(2020) Minliang Liu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data

(2020) Liu Yang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

hp-VPINNs: Variational physics-informed neural networks with domain decomposition

(2020) Ehsan Kharazmi et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Estimating model inadequacy in ordinary differential equations with physics-informed neural networks

(2020) Felipe A.C. Viana et al.   COMPUTERS & STRUCTURES

Optimal Energy Routing Design in Energy Internet with Multiple Energy Routing Centers Using Artificial Neural Network-Based Reinforcement Learning Method

(2019) Dan-Lu Wang et al.   Applied Sciences-Basel

A Review of Information Fusion Methods for Gas Turbine Diagnostics

(2019) Valentina Zaccaria et al.   Sustainability

Physics-informed neural networks for high-speed flows

(2019) Zhiping Mao et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A machine learning framework to forecast wave conditions

(2018) Scott C. James et al.   COASTAL ENGINEERING

Hidden physics models: Machine learning of nonlinear partial differential equations

(2018) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations

(2018) Maziar Raissi et al.   SIAM JOURNAL ON SCIENTIFIC COMPUTING

ThermalNet: A deep reinforcement learning-based combustion optimization system for coal-fired boiler

(2018) Yin Cheng et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A unified deep artificial neural network approach to partial differential equations in complex geometries

(2018) Jens Berg et al.   NEUROCOMPUTING

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Inferring solutions of differential equations using noisy multi-fidelity data

(2017) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Assessing the maturity of a research area: bibliometric review and proposed framework

(2016) Heather Keathley-Herring et al.   SCIENTOMETRICS