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Physics Informed Neural Network using Finite Difference Method
Arxiv
0+阅读 · 2月25日
PBPK-iPINNs: Inverse Physics-Informed Neural Networks for Physiologically Based Pharmacokinetic Brain Models
Arxiv
0+阅读 · 2月22日
Enhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results
Arxiv
0+阅读 · 3月3日
Deep Reinforcement Learning for Optimizing Energy Consumption in Smart Grid Systems
Arxiv
0+阅读 · 2月20日
Comparative Analysis of Wave Scattering Numerical Modeling Using the Boundary Element Method and Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月20日
Astral: training physics-informed neural networks with error majorants
Arxiv
0+阅读 · 3月2日
Efficient Aircraft Design Optimization Using Multi-Fidelity Models and Multi-fidelity Physics Informed Neural Networks
Arxiv
0+阅读 · 2月28日
Stabilized Adaptive Loss and Residual-Based Collocation for Physics-Informed Neural Networks
Arxiv
0+阅读 · 3月3日
Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction
Arxiv
0+阅读 · 2月23日
Hybrid Model Predictive Control with Physics-Informed Neural Network for Satellite Attitude Control
Arxiv
0+阅读 · 2月17日
Investigating Nonlinear Quenching Effects on Polar Field Buildup in the Sun Using Physics-Informed Neural Networks
Investigating Nonlinear Quenching Effects on Polar Field Buildup in the Sun Using Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月18日
Drug Release Modeling using Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月10日
Do physics-informed neural networks (PINNs) need to be deep? Shallow PINNs using the Levenberg-Marquardt algorithm
Arxiv
0+阅读 · 2月9日
Do physics-informed neural networks (PINNs) need to be deep? Shallow PINNs using the Levenberg-Marquardt algorithm
Arxiv
0+阅读 · 2月11日
Statistical Learning Analysis of Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月11日
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