dgm2

sounds good, thanks! What would be the best way to replicate something like the following Dionysus code with GUDHI ? 1) get persistence diagram e.g. d1: ``` from dionysus import...

hello, any workaround for this issue? I found this assertion error as well on cuda 10.2 ` edge_index, edge_weight = spspmm(edge_index, edge_weight, edge_index, edge_weight, num_nodes, num_nodes, num_nodes)` ``` File "/mnt/iusers01/fse-ugpgt01/compsci01/xxxx/.conda/envs/graph_ae/lib/python3.7/site-packages/torch_sparse/spspmm.py",...

the torch version is giving an error about size. it expects the last index of crow to be 8629? any idea on how get this to work with the torch...

I tried converting the SparseTensors > row, col, value = torch.sparse.mm(A.to_torch_sparse_csr_tensor(), B.to_torch_sparse_csr_tensor()) gives > return torch._sparse_mm(mat1, mat2) > RuntimeError: torch.empty: Only 2D sparse CSR tensors are supported.

thanks! the callback method returns `stills, frames, image` how should I input these into `plot_dataset_traversals` ? or into `visualize_dataset_traversal` or what is are corresponding values there? e.g. does `stills` corresponds...

for example, see left and bottom ? how to solarize those parts  many thanks!

My question is how to compare multiple residuals via the plot as you have in tutorial2 and tutorial3. The issue with current code is that the residuals can be positive...

Hello, does the residual plot usually reflect the same result as the loss plot? what would it mean to have lower loss but higher error in the residual? or this...

Hi, thanks for the answer. Could you share a minimal python snippet to generate `Data_KS.mat` using `scipy.integrate.solve_ivp` please? Many thanks!