Comments (4)
Where did the mean field game issue go?
from neuralpde.jl.
Indeed, now that it's starting to get documented, feel free to just post some test problems and see if it's working on them. We need to keep pushing the strategies in different ways. #46 is still the most puzzling thing!
from neuralpde.jl.
The EmoryMLIP/MFGnet.jl#2 has been idle since March 2 but NeuralNetDiffEq is close to solving this one without looking over their shoulders.
I suggest addressing all the test models from here: https://arxiv.org/pdf/1811.08782.pdf. You have already dealt with the DGM method very efficiently in the UDE paper. Nevertheless, the set of test problems is good. NeuralNetDiffEq would need to add: Fokker-Planck (Kolmogorov forward), Systemic risk and Mean Field Games (FBSDE system of HJB+FP).
Still linking all these test problem is #52 which should be music to @KirillZubov in terms of similar steps to PINNs. You can save time by eliminating inefficient steps in their work like local solvers and expectation/weak solution. This stuff is already up and running on github/Python and can be a good benchmark for Julia/NeuralNetDiffEq (they are using massive GPU power though).
from neuralpde.jl.
I'm not sure what's actionable here.
from neuralpde.jl.
Related Issues (20)
- Importing NeuralPDE.jl before Interpolations.jl can lead to an error
- Problem in replicating INVERSE PROBELM tutorial on ODE HOT 23
- Parameter Estimation in NNODE
- Parameter Estimation formulation in PINNs HOT 5
- Documentation for BayesianPINN and ahmc_bayesian_pinn_pde
- Encountering Precompilation Error Messages When Adding NeuralPDE Package in Julia HOT 3
- Distance functions as a description of complex geometries HOT 1
- Bump CUDA Compat HOT 1
- How can I solve complex-valued ordinary differential equations (ODEs) using neural networks, given limitations with complex data types in libraries like Lux? HOT 7
- Can't get the @named pde_system to work with a ode system HOT 4
- Add support for equations with complex numbers HOT 20
- Neural Adapter Documentation Example Not Working HOT 6
- DGM Tutorial fails HOT 2
- KeyError when solving Parameter Identification problem using NeuralPDE.jl HOT 9
- Linear parabolic example throws an error on new julia install HOT 2
- NeuralPDE slows when using old weights and biases on a new but related ode HOT 3
- NeuralPDE with LuxAMDGPU, Optimize.solve throws error
- GPU Compatibility Issue: Compilation Error with Complex-Valued Data in LuxCUDA Broadcasting Kernel HOT 8
- Tutorial: imposing constraint on PINN solution of Fokker Planck fails HOT 5
- The trial solutions to additional_loss function are different depending on parameters
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