Comments (2)
NNPDENS
with EM
is the same as DBDP2
. We should probably just make the test run a bit longer though.
from neuralpde.jl.
Tests are more robust now.
from neuralpde.jl.
Related Issues (20)
- 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 4
- The trial solutions to additional_loss function are different depending on parameters
- API PINO PDE HOT 5
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from neuralpde.jl.