VVeida / RK4_PINNLinks
☆12Updated last year
Alternatives and similar repositories for RK4_PINN
Users that are interested in RK4_PINN are comparing it to the libraries listed below
Sorting:
- ☆131Updated 3 years ago
- Research/development of physics-informed neural networks for dynamic systems☆29Updated 10 months ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆92Updated 2 years ago
- Implementing a physics-informed DeepONet from scratch☆46Updated 2 years ago
- ☆87Updated last year
- ☆21Updated 2 years ago
- Physics-informed neural networks package☆325Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆152Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆78Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆89Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆250Updated 3 years ago
- Boosting the training of physics informed neural networks with transfer learning☆26Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆156Updated last year
- Deep learning assisted dynamic mode decomposition☆19Updated 4 years ago
- Optimal Control with PDEs solved by a Differentiable Solver☆11Updated last year
- mathLab mirror of Python Dynamic Mode Decomposition☆105Updated 7 months ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- Basic implementation of physics-informed neural network with pytorch.☆79Updated 3 years ago
- Code for Rice et al. 2020 "Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forcea…☆36Updated 3 weeks ago
- ☆34Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆27Updated 2 years ago
- Generative Pre-Trained Physics-Informed Neural Networks Implementation☆104Updated last month
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆117Updated last year
- In recent years, the use of physics-informed neural networks (PINNs) has gained popularity across several engineering disciplines due to …☆10Updated 2 years ago
- A library for Koopman Neural Operator with Pytorch.☆303Updated last year
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆10Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆37Updated 2 years ago
- The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks☆38Updated 3 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago