* add RBF implementation in pytorch (in layers)
* add POD-RBF example (baseline for nonintrusive closure)
* Add POD only and POD+RBF implementation
* add POD-RBF in tutorial 8
* gpinn/basepinn new classes, pinn restructure
* codacy fix gpinn/basepinn/pinn
* inverse problem fix
* Causal PINN (#267)
* fix GPU training in inverse problem (#283)
* Create a `compute_residual` attribute for `PINNInterface`
* Modify dataloading in solvers (#286)
* Modify PINNInterface by removing _loss_phys, _loss_data
* Adding in PINNInterface a variable to track the current condition during training
* Modify GPINN,PINN,CausalPINN to match changes in PINNInterface
* Competitive Pinn Addition (#288)
* fixing after rebase/ fix loss
* fixing final issues
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Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
* Modify min max formulation to max min for paper consistency
* Adding SAPINN solver (#291)
* rom solver
* fix import
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Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
Co-authored-by: Anna Ivagnes <75523024+annaivagnes@users.noreply.github.com>
Co-authored-by: valc89 <103250118+valc89@users.noreply.github.com>
Co-authored-by: Monthly Tag bot <mtbot@noreply.github.com>
Co-authored-by: Nicola Demo <demo.nicola@gmail.com>
* Unify integral kernel NO architectures with NeuralKernelOperator
* Implement FNO based on NeuralKernelOperator
* modify doc for FNO and add for FourierIntegralKernel, NeuralKernelOperator
* adding tests
---------
Co-authored-by: Dario Coscia <dariocoscia@Dario-Coscia.local>
Co-authored-by: Dario Coscia <dariocoscia@dhcp-015.eduroam.sissa.it>
