Image de couverture de livre

Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	An, Kang, Si, Chenhao, Ma, Shiqian, Yan, Ming
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

AutoBalance: An Automatic Balancing Framework for Training Physics-Informed Neural Networks
par: An, Kang, et autres
Publié: (2025)

Complex Physics-Informed Neural Network
par: Si, Chenhao, et autres
Publié: (2025)

Initialization-enhanced Physics-Informed Neural Network with Domain Decomposition (IDPINN)
par: Si, Chenhao, et autres
Publié: (2024)

Improved Training of Physics-Informed Neural Networks with Model Ensembles
par: Haitsiukevich, Katsiaryna, et autres
Publié: (2022)

Rethinking Input Domains in Physics-Informed Neural Networks via Geometric Compactification Mappings
par: Huang, Zhenzhen, et autres
Publié: (2026)

naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement
par: Kim, Hankyeol, et autres
Publié: (2026)

Revisiting Heat Flux Analysis of Tungsten Monoblock Divertor on EAST using Physics-Informed Neural Network
par: Wang, Xiao, et autres
Publié: (2025)

Physics-Informed Neural Networks and Extensions
par: Raissi, Maziar, et autres
Publié: (2024)

Physics-Informed Neural Networks with Architectural Physics Embedding for Large-Scale Wave Field Reconstruction
par: Zhang, Huiwen, et autres
Publié: (2026)

Neural Force Field: Few-shot Learning of Generalized Physical Reasoning
par: Li, Shiqian, et autres
Publié: (2025)

SeqBattNet: A Discrete-State Physics-Informed Neural Network with Aging Adaptation for Battery Modeling
par: Tran, Khoa, et autres
Publié: (2025)

Demystifying Manifold Constraints in LLM Pre-training
par: An, Kang, et autres
Publié: (2026)

Densely Multiplied Physics Informed Neural Networks
par: Jiang, Feilong, et autres
Publié: (2024)

Actor-Critic based Online Data Mixing For Language Model Pre-Training
par: Ma, Jing, et autres
Publié: (2025)

Physics-Informed Graph Neural Networks for Water Distribution Systems
par: Ashraf, Inaam, et autres
Publié: (2024)

Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks
par: Mazandarani, Mehran, et autres
Publié: (2025)

Learning without Global Backpropagation via Synergistic Information Distillation
par: Ye, Chenhao, et autres
Publié: (2025)

Evidential Physics-Informed Neural Networks
par: Tan, Hai Siong, et autres
Publié: (2025)

Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification
par: Qu, Jintao, et autres
Publié: (2025)

Physics-Informed Neural Networks with Learnable Loss Balancing and Transfer Learning
par: Pirayeshshirazinezhad, Reza
Publié: (2026)

Physics-Informed Neural Network Surrogate Models for River Stage Prediction
par: Zoch, Maximilian, et autres
Publié: (2025)

Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
par: Miranda, Miro, et autres
Publié: (2024)

GINN-KAN: Interpretability pipelining with applications in Physics Informed Neural Networks
par: Ranasinghe, Nisal, et autres
Publié: (2024)

L-MoE: End-to-End Training of a Lightweight Mixture of Low-Rank Adaptation Experts
par: Ji, Shihao, et autres
Publié: (2025)

HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
par: Ma, Yihong, et autres
Publié: (2023)

LION-DG: Layer-Informed Initialization with Deep Gradient Protocols for Accelerated Neural Network Training
par: Kim, Hyunjun
Publié: (2026)

QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation
par: Xu, Chenhui, et autres
Publié: (2024)

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
par: Cho, Yeseul, et autres
Publié: (2025)

Robotic World Model: A Neural Network Simulator for Robust Policy Optimization in Robotics
par: Li, Chenhao, et autres
Publié: (2025)

DiffGrad for Physics-Informed Neural Networks
par: Rahman, Jamshaid Ul, et autres
Publié: (2024)

Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
par: Ganguly, Abhisek, et autres
Publié: (2026)

iPINNER: An Iterative Physics-Informed Neural Network with Ensemble Kalman Filter
par: Lu, Binghang, et autres
Publié: (2025)

Mask-PINNs: Mitigating Internal Covariate Shift in Physics-Informed Neural Networks
par: Jiang, Feilong, et autres
Publié: (2025)

Limitations of Physics-Informed Neural Networks: a Study on Smart Grid Surrogation
par: Cestero, Julen, et autres
Publié: (2025)

Drug Release Modeling using Physics-Informed Neural Networks
par: Qureshi, Daanish Aleem, et autres
Publié: (2026)

Physics-Guided Geometric Diffusion for Macro Placement Generation
par: Yoon, Jongho, et autres
Publié: (2026)

Total Variation Rates for Riemannian Flow Matching
par: Guan, Yunrui, et autres
Publié: (2026)

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations
par: Wei, Zhao, et autres
Publié: (2026)

Modeling COVID-19 Dynamics in German States Using Physics-Informed Neural Networks
par: Rothenbeck, Phillip, et autres
Publié: (2025)

MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting
par: Nguyen, Thang, et autres
Publié: (2024)