Prakhar Sharma
Prakhar Sharma
Any PDE is combination of derivative of output layers with respect to input layers. So if you are solving 2D fluid flow, the inputs will be x and y, whereas...
Yes, you just need to read the first line of the docs [here](https://github.com/lululxvi/deepxde/blob/e030a3d8d3503bfca006c505271cefa827833ec5/deepxde/gradients.py#L259C34-L259C60). It says, ``` H[i][j] = d^2y / dx_i dx_j ``` With component you can decide which `y`...
No it is not. But if you have a code you can modify it. But what is Parallel nets, is it XPINN, CPINN or something else?
Yes sure. First clone the DeepXDE repository and create/ copy a python file for your problem in the root directory of the repo. Open the [optimizers.py](https://github.com/lululxvi/deepxde/blob/master/deepxde/optimizers/pytorch/optimizers.py) file in your repo....
https://yaleedu-my.sharepoint.com/:f:/g/personal/lu_lu_yale_edu/EnTn0aLimaRJuNKDOc0lfHkB2MXK8n8vAO1oV5cWVdJo3w?e=OLp80r the link is already provided in the docs. 
Because LBFGS is implemented differently in both libraries. You find the link the the particular implementation (papers) in the source code of tf and torch.
PINNs were originally proposed to replace PDE solvers, meaning no analytical solution is required. This is very different from conventional supervised PDE solvers such as unet, FEDformer, FNO where you...
This is the problem. ```python y_pred_value = model.predict(x) ``` Can you show me your PDE please?
```sh dde.saveplot(losshistory, train_state, issave=True, isplot=False) ``` This will save the loss history in `loss.dat`, the predicted solution with the best model in `test.dat`. For plotting you can use matplotlib.
Once you have the dat file, you can do whatever you want. Paraview has so many filter to plot CSV file, but that is out of scope of this discussion....