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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
Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月10日
On the Role of Consistency Between Physics and Data in Physics-Informed Neural Networks
Arxiv
0+阅读 · 2月11日
A Unified Physics-Informed Neural Network for Modeling Coupled Electro- and Elastodynamic Wave Propagation Using Three-Stage Loss Optimization
Arxiv
0+阅读 · 2月14日
Visualizing the loss landscapes of physics-informed neural networks
Arxiv
0+阅读 · 2月5日
Bayesian PINNs for uncertainty-aware inverse problems (BPINN-IP)
Arxiv
0+阅读 · 2月4日
Conformal mapping based Physics-informed neural networks for designing neutral inclusions
Arxiv
0+阅读 · 2月2日
Physics-Informed Neural Networks and Neural Operators for Parametric PDEs
Arxiv
0+阅读 · 1月30日
SPIKE: Sparse Koopman Regularization for Physics-Informed Neural Networks
Arxiv
0+阅读 · 1月16日
SPIKE: Sparse Koopman Regularization for Physics-Informed Neural Networks
Arxiv
0+阅读 · 1月15日
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