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Scientific Machine Learning through Physics-Informed Neural Networks:
  Where we are and What's next
v1v2v3v4 (latest)

Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next

Journal of Scientific Computing (J. Sci. Comput.), 2022
14 January 2022
S. Cuomo
Vincenzo Schiano Di Cola
F. Giampaolo
G. Rozza
Maizar Raissi
F. Piccialli
    PINN
ArXiv (abs)PDFHTMLGithub (2381★)

Papers citing "Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next"

50 / 412 papers shown
Operator Learning at Machine Precision
Operator Learning at Machine Precision
Aras Bacho
Aleksei G. Sorokin
Xianjin Yang
Théo Bourdais
Edoardo Calvello
Matthieu Darcy
Alexander Hsu
Bamdad Hosseini
H. Owhadi
160
3
0
25 Nov 2025
Terminal Velocity Matching
Terminal Velocity Matching
Linqi Zhou
Mathias Parger
Ayaan Haque
Jiaming Song
137
4
0
24 Nov 2025
Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models
Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models
Perceval Beja-Battais
Alain Grossetête
Nicolas Vayatis
MedImAI4CE
266
1
0
20 Nov 2025
PCARNN-DCBF: Minimal-Intervention Geofence Enforcement for Ground Vehicles
PCARNN-DCBF: Minimal-Intervention Geofence Enforcement for Ground Vehicles
Yinan Yu
Samuel Scheidegger
AI4CE
265
0
0
19 Nov 2025
Physics-Constrained Adaptive Neural Networks Enable Real-Time Semiconductor Manufacturing Optimization with Minimal Training Data
Physics-Constrained Adaptive Neural Networks Enable Real-Time Semiconductor Manufacturing Optimization with Minimal Training Data
Rubén Darío Guerrero
83
0
0
16 Nov 2025
Convomem Benchmark: Why Your First 150 Conversations Don't Need RAG
Convomem Benchmark: Why Your First 150 Conversations Don't Need RAGJournal of the mechanics and physics of solids (JMPS), 2025
Egor Pakhomov
Erik Nijkamp
Caiming Xiong
393
3
0
13 Nov 2025
When is a System Discoverable from Data? Discovery Requires Chaos
When is a System Discoverable from Data? Discovery Requires Chaos
Zakhar Shumaylov
Peter Zaika
Philipp Scholl
Gitta Kutyniok
Lior Horesh
Carola-Bibiane Schönlieb
244
7
0
12 Nov 2025
From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
Ruyin Wan
G. Karniadakis
P. Stinis
163
0
0
10 Nov 2025
Physics-Informed Neural Networks for Speech Production
Physics-Informed Neural Networks for Speech Production
Kazuya Yokota
Ryosuke Harakawa
Masaaki Baba
Masahiro Iwahashi
133
0
0
01 Nov 2025
PDE-SHARP: PDE Solver Hybrids through Analysis and Refinement Passes
PDE-SHARP: PDE Solver Hybrids through Analysis and Refinement Passes
Shaghayegh Fazliani
Madeleine Udell
269
1
0
31 Oct 2025
A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning: Z24 Bridge structural health monitoring benchmark validation
A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning: Z24 Bridge structural health monitoring benchmark validationStructural And Multidisciplinary Optimization (SMO), 2025
Marios Impraimakis
Evangelia Nektaria Palkanoglou
156
2
0
30 Oct 2025
Mixture-of-Experts Operator Transformer for Large-Scale PDE Pre-Training
Mixture-of-Experts Operator Transformer for Large-Scale PDE Pre-Training
Hong Wang
Haiyang Xin
Jie Wang
Xuanze Yang
Fei Zha
Huanshuo Dong
Yan Jiang
MoEAI4CE
744
5
0
29 Oct 2025
FlowCapX: Physics-Grounded Flow Capture with Long-Term Consistency
FlowCapX: Physics-Grounded Flow Capture with Long-Term Consistency
Ningxiao Tao
Liru Zhang
Xingyu Ni
Mengyu Chu
Baoquan Chen
121
0
0
27 Oct 2025
Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method
Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method
Diego Marcondes
157
0
0
27 Oct 2025
Self-induced stochastic resonance: A physics-informed machine learning approach
Self-induced stochastic resonance: A physics-informed machine learning approach
Divyesh Savaliya
Marius E. Yamakou
124
1
0
26 Oct 2025
PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling
PINN Balls: Scaling Second-Order Methods for PINNs with Domain Decomposition and Adaptive Sampling
Andrea Bonfanti
Ismael Medina
Roman List
Björn Staeves
Roberto Santana
M. Ellero
161
0
0
24 Oct 2025
Physics-Informed Large Language Models for HVAC Anomaly Detection with Autonomous Rule Generation
Physics-Informed Large Language Models for HVAC Anomaly Detection with Autonomous Rule Generation
Subin Lin
Chuanbo Hua
AI4CE
141
0
0
20 Oct 2025
Deep Neural ODE Operator Networks for PDEs
Deep Neural ODE Operator Networks for PDEs
Ziqian Li
Kang Liu
Yongcun Song
Hangrui Yue
Enrique Zuazua
AI4CE
187
0
0
17 Oct 2025
APRIL: Auxiliary Physically-Redundant Information in Loss - A physics-informed framework for parameter estimation with a gravitational-wave case study
APRIL: Auxiliary Physically-Redundant Information in Loss - A physics-informed framework for parameter estimation with a gravitational-wave case study
Matteo Scialpi
Francesco Di Clemente
Leigh Smith
Michał Bejger
145
0
0
15 Oct 2025
Physics-augmented Multi-task Gaussian Process for Modeling Spatiotemporal Dynamics
Physics-augmented Multi-task Gaussian Process for Modeling Spatiotemporal Dynamics
Xizhuo Zhang
Bing Yao
AI4CE
153
0
0
15 Oct 2025
General Fourier Feature Physics-Informed Extreme Learning Machine (GFF-PIELM) for High-Frequency PDEs
General Fourier Feature Physics-Informed Extreme Learning Machine (GFF-PIELM) for High-Frequency PDEs
Fei Ren
Sifan Wang
Pei-Zhi Zhuang
H. Yu
He Yang
AI4CE
181
0
0
14 Oct 2025
Learning Operators through Coefficient Mappings in Fixed Basis Spaces
Learning Operators through Coefficient Mappings in Fixed Basis Spaces
Chuqi Chen
Yang Xiang
Weihong Zhang
170
1
0
11 Oct 2025
"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
Luke Stevenson
Sanchari Das
194
1
0
07 Oct 2025
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
Bongseok Kim
Jiahao Zhang
Guang Lin
132
1
0
03 Oct 2025
Training Variation of Physically-Informed Deep Learning Models
Training Variation of Physically-Informed Deep Learning Models
Ashley Lenau
Dennis Dimiduk
Stephen R. Niezgoda
177
0
0
03 Oct 2025
Aspects of holographic entanglement using physics-informed-neural-networks
Aspects of holographic entanglement using physics-informed-neural-networks
Anirudh Deb
Yaman Sanghavi
PINN
203
3
0
29 Sep 2025
Stabilizing Humanoid Robot Trajectory Generation via Physics-Informed Learning and Control-Informed Steering
Stabilizing Humanoid Robot Trajectory Generation via Physics-Informed Learning and Control-Informed Steering
Evelyn DÉlia
Paolo Maria Viceconte
Lorenzo Rapetti
Diego Ferigo
Giulio Romualdi
Giuseppe L’Erario
Raffaello Camoriano
Daniele Pucci
121
0
0
29 Sep 2025
A study of Universal ODE approaches to predicting soil organic carbon
A study of Universal ODE approaches to predicting soil organic carbon
Satyanarayana Raju G.V.V
Prathamesh Dinesh Joshi
Raj Abhijit Dandekar
Rajat Dandekar
Sreedath Panat
AI4CE
167
0
0
29 Sep 2025
Fast-Forward Lattice Boltzmann: Learning Kinetic Behaviour with Physics-Informed Neural Operators
Fast-Forward Lattice Boltzmann: Learning Kinetic Behaviour with Physics-Informed Neural Operators
Xiao Xue
Marco F.P. ten Eikelder
Mingyang Gao
Xiaoyuan Cheng
Yiming Yang
Yi He
Shuo Wang
Sibo Cheng
Yukun Hu
Peter V. Coveney
AI4CE
159
1
0
26 Sep 2025
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
Yi En Chou
Te Hsin Liu
Chao An Lin
PINNAI4CE
199
2
0
24 Sep 2025
Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems
Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems
Aleksandra Jekic
Afroditi Natsaridou
Signe Riemer-Sørensen
Helge Langseth
Odd Erik Gundersen
PINNAI4CE
247
2
0
24 Sep 2025
Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints
Physics-informed time series analysis with Kolmogorov-Arnold Networks under Ehrenfest constraints
Abhijit Sen
Illya V. Lukin
K. Jacobs
Lev Kaplan
Andrii G. Sotnikov
Denys I. Bondar
AI4TSAI4CE
143
0
0
23 Sep 2025
Domain-Informed Genetic Superposition Programming: A Case Study on SFRC Beams
Domain-Informed Genetic Superposition Programming: A Case Study on SFRC Beams
M. S. Khorshidi
Navid Yazdanjue
Hassan Gharoun
M. Nikoo
Fang Chen
Amir H. Gandomi
AI4CE
171
0
0
20 Sep 2025
A Neural Network for the Identical Kuramoto Equation: Architectural Considerations and Performance Evaluation
A Neural Network for the Identical Kuramoto Equation: Architectural Considerations and Performance Evaluation
Nishantak Panigrahi
Mayank Patwal
116
0
0
17 Sep 2025
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
Yifan Yu
Cheuk Hin Ho
Yangshuai Wang
AI4CE
319
2
0
17 Sep 2025
Unified Spatiotemporal Physics-Informed Learning (USPIL): A Framework for Modeling Complex Predator-Prey Dynamics
Unified Spatiotemporal Physics-Informed Learning (USPIL): A Framework for Modeling Complex Predator-Prey Dynamics
Julian Evan Chrisnanto
Salsabila Rahma Alia
Yulison Herry Chrisnanto
Ferry Faizal
PINNAI4CE
415
1
0
16 Sep 2025
PINGS: Physics-Informed Neural Network for Fast Generative Sampling
PINGS: Physics-Informed Neural Network for Fast Generative Sampling
Achmad Ardani Prasha
Clavino Ourizqi Rachmadi
Muhamad Fauzan Ibnu Syahlan
Naufal Rahfi Anugerah
Nanda Garin Raditya
Putri Amelia
Sabrina Laila Mutiara
Hilman Syachr Ramadhan
DiffM3DGS
113
0
0
14 Sep 2025
Physics-Informed Neural Networks vs. Physics Models for Non-Invasive Glucose Monitoring: A Comparative Study Under Noise-Stressed Synthetic Conditions
Physics-Informed Neural Networks vs. Physics Models for Non-Invasive Glucose Monitoring: A Comparative Study Under Noise-Stressed Synthetic Conditions
Riyaadh Gani
93
0
0
12 Sep 2025
Variational Neural Networks for Observable Thermodynamics (V-NOTS)
Variational Neural Networks for Observable Thermodynamics (V-NOTS)
Christopher Eldred
François Gay-Balmaz
V. Putkaradze
PINNAI4CE
209
0
0
11 Sep 2025
Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
Mominul Rubel
Adam Meyers
Gabriel Nicolosi
AI4CE
98
0
0
10 Sep 2025
IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation
IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation
Shalev Manor
Mohammad Kohandel
PINN
199
0
0
08 Sep 2025
Neuro-Spectral Architectures for Causal Physics-Informed Networks
Neuro-Spectral Architectures for Causal Physics-Informed Networks
Arthur Bizzi
Leonardo M. Moreira
Márcio Marques
Leonardo Mendonça
Christian Júnior de Oliveira
...
Daniel Yukimura
Pavel Petrov
João M. Pereira
Tiago Novello
Lucas Nissenbaum
PINN
407
2
0
05 Sep 2025
RAMS: Residual-based adversarial-gradient moving sample method for scientific machine learning in solving partial differential equations
RAMS: Residual-based adversarial-gradient moving sample method for scientific machine learning in solving partial differential equations
Weihang Ouyang
Min Zhu
Wei Xiong
Si-Wei Liu
Lu Lu
268
3
0
01 Sep 2025
The Need for Verification in AI-Driven Scientific Discovery
The Need for Verification in AI-Driven Scientific Discovery
Cristina Cornelio
Takuya Ito
Ryan Cory-Wright
S. Dash
L. Horesh
237
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0
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Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data
Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data
Anastasis Kratsios
Tin Sum Cheng
Daniel Roy
AAML
200
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0
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Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements
Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements
Xuyang Li
Mahdi Masmoudi
Rami Gharbi
N. Lajnef
Vishnu Boddeti
AI4CE
203
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Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks
Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks
Bangti Jin
Longjun Wu
184
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Physics-Constrained Machine Learning for Chemical Engineering
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Victor M. Zavala
PINNAI4CE
262
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Error analysis for the deep Kolmogorov method
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Thang Do
Lukas Gonon
Arnulf Jentzen
Ionel Popescu
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Neural Robot Dynamics
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Eric Heiden
Iretiayo Akinola
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Miles Macklin
Yashraj S. Narang
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