Imagen de Portada

Recent Advances of NeuroDiffEq -- An Open-Source Library for Physics-Informed Neural Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Liu, Shuheng, Protopapas, Pavlos, Sondak, David, Chen, Feiyu
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Stiff Transfer Learning for Physics-Informed Neural Networks
por: Seiler, Emilien, et al.
Publicado: (2025)

Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles
por: Flores, Pablo, et al.
Publicado: (2025)

PTL-PINNs: Perturbation-Guided Transfer Learning with Physics- Informed Neural Networks for Nonlinear Systems
por: Alexandrino, Duarte, et al.
Publicado: (2026)

One-Shot Transfer Learning for Nonlinear PDEs with Perturbative PINNs
por: Auroy, Samuel, et al.
Publicado: (2025)

Gradient Scaling Effects in Adaptive Spectral PINNs for Stiff Nonlinear ODEs
por: Yepes, Isabela M., et al.
Publicado: (2026)

Chebyshev-Augmented One-Shot Transfer Learning for PINNs on Nonlinear Differential Equations
por: Rao, Yiqi, et al.
Publicado: (2026)

DiffGrad for Physics-Informed Neural Networks
por: Rahman, Jamshaid Ul, et al.
Publicado: (2024)

Gravitational Duals from Equations of State
por: Bea, Yago, et al.
Publicado: (2024)

EqOD: Symmetry-Informed Stability Selection for PDE Identification
por: N'guessan, Gnankan Landry Regis, et al.
Publicado: (2026)

RED-DiffEq: Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversion
por: Shan, Siming, et al.
Publicado: (2025)

BI-EqNO: Generalized Approximate Bayesian Inference with an Equivariant Neural Operator Framework
por: Zhou, Xu-Hui, et al.
Publicado: (2024)

NeuroRisk: Physics-Informed Neural Optimization for Risk-Aware Traffic Engineering
por: Mao, Yingming, et al.
Publicado: (2026)

Learning embeddings of non-linear PDEs: the Burgers' equation
por: Tarancón-Álvarez, Pedro, et al.
Publicado: (2026)

MuonEq: Balancing Before Orthogonalization with Lightweight Equilibration
por: Chang, Da, et al.
Publicado: (2026)

EqCollide: Equivariant and Collision-Aware Deformable Objects Neural Simulator
por: Chen, Qianyi, et al.
Publicado: (2025)

jinns: a JAX Library for Physics-Informed Neural Networks
por: Gangloff, Hugo, et al.
Publicado: (2024)

Advancing Solutions for the Three-Body Problem Through Physics-Informed Neural Networks
por: Pereira, Manuel Santos, et al.
Publicado: (2025)

Physics-Informed Neural Networks for Joint Source and Parameter Estimation in Advection-Diffusion Equations
por: Anague, Brenda, et al.
Publicado: (2025)

Neuro-Spectral Architectures for Causal Physics-Informed Networks
por: Bizzi, Arthur, et al.
Publicado: (2025)

Recent Advances in Hypergraph Neural Networks
por: Yang, Murong, et al.
Publicado: (2025)

EqDrive: Efficient Equivariant Motion Forecasting with Multi-Modality for Autonomous Driving
por: Wang, Yuping, et al.
Publicado: (2023)

Conformalized Physics-Informed Neural Networks
por: Podina, Lena, et al.
Publicado: (2024)

Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation
por: Zong, Yifei, et al.
Publicado: (2024)

Preconditioning for Physics-Informed Neural Networks
por: Liu, Songming, et al.
Publicado: (2024)

Statistical Learning Analysis of Physics-Informed Neural Networks
por: Barajas-Solano, David A.
Publicado: (2026)

Exact and approximate error bounds for physics-informed neural networks
por: Chantada, Augusto T., et al.
Publicado: (2024)

Dual-Balancing for Physics-Informed Neural Networks
por: Zhou, Chenhong, et al.
Publicado: (2025)

Curriculum Learning of Physics-Informed Neural Networks based on Spatial Correlation
por: Chen, Xujia, et al.
Publicado: (2026)

Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks
por: Zhao, Yequan, et al.
Publicado: (2025)

Efficient PINNs via Multi-Head Unimodular Regularization of the Solutions Space
por: Tarancón-Álvarez, Pedro, et al.
Publicado: (2025)

Advancing Physics Data Analysis through Machine Learning and Physics-Informed Neural Networks
por: Vatellis, Vasileios
Publicado: (2024)

From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning
por: Toscano, Juan Diego, et al.
Publicado: (2024)

Complex Physics-Informed Neural Network
por: Si, Chenhao, et al.
Publicado: (2025)

Physics-Informed Neural Networks and Extensions
por: Raissi, Maziar, et al.
Publicado: (2024)

EqDeepRx: Learning a Scalable MIMO Receiver
por: Honkala, Mikko, et al.
Publicado: (2026)

Open-Source Fermionic Neural Networks with Ionic Charge Initialization
por: Pranesh, Shai, et al.
Publicado: (2024)

Physical Informed Neural Networks for modeling ocean pollutant
por: Battina, Karishma, et al.
Publicado: (2025)

Fourier Feature Pyramids for Physics-Informed Neural Networks
por: Zhao, Brandon, et al.
Publicado: (2026)

Functional Tensor Decompositions for Physics-Informed Neural Networks
por: Vemuri, Sai Karthikeya, et al.
Publicado: (2024)

Architectural Strategies for the optimization of Physics-Informed Neural Networks
por: Saratchandran, Hemanth, et al.
Publicado: (2024)