Photon-AI-Research/NeuralSolvers
Neural network based solvers for partial differential equations and inverse problems :milky_way:. Implementation of physics-informed neural networks in pytorch.
3 Releases
Latest: 3y ago
Geometries and Adaptive Sampling v.0.1.2Latest
StillerPatrick·3y ago·November 7, 2022We added Geometries as a new interface for the PDE dataset. This allows a generic inference pipeline and reduces the amount of code to solve a PDE with NeuralSolvers. This includes various sampling methods and brings adaptive sampling into Neural Solvers. Furthermore, we improved the prints and the logging features.
Tensorboard-logging, gradient visualisation, bugfixesv.0.1.1
StillerPatrick·4y ago·October 28, 2021✨ New Features
- Tensorboard logging is available and can be activated in the `fit()` function. Logger enables automatic tracking of all loss terms and their weights
- Logging of Loss gradients in order to identity gradient pathologies, you can track the gradient updates by adding a logger and setting the
- track_gradient flag in the `fit()` function.
🐛 Bugfixes
- Fix the usage of the `to` method in MLP and FingerNet
📦 Examples
- A working example of the heat equation
- #48
- #41
Learning Rate Annealing, Logger, Callbacks and Bugfixesv.0.1
StillerPatrick·4y ago·September 6, 2021✨ New Features
- Pretraining the `fit()` function allows a pretraining by optimizing only on the initial condition
- Callbacks its possible to write custom callbacks in order to modify the behavior in the training loop. At the moment only callbacks at the end of epochs are supported
🐛 Bugfixes
- Fix the bug in the calculation of neumann and robin boundary condition
📦 Examples
- A working example of burgers equation
📦 Resolved issues
- issue #24
- issue #19
- issue #13
- issue #30
- issue #31