Issues
- 5
- 0
`IndexError` when using `torch_cuda` backend
#65 opened by const7 - 0
`ColumnKernelizer` failed with sklearn 1.5
#59 opened by yuerout - 0
Need to fix cupy types
#55 opened by mvdoc - 1
Optimized Model Saving to/Loading from Disk
#53 opened by MShinkle - 2
Convert model from GPU to CPU
#52 opened by tommybotch - 11
torch MPS backend support
#42 opened by emdupre - 0
Write more examples
#4 opened by TomDLT - 0
- 3
- 1
MultipleKernelRidgeCV - bug with solver_params
#38 opened by iyttor - 1
Add some warnings if n<p and if n>p
#13 opened by TomDLT - 1
Reduce computing time of examples on CPU
#30 opened by mvdoc - 0
Add more github actions
#28 opened by TomDLT - 2
Make docs/examples cpu friendly
#27 opened by mvdoc - 1
- 0
Make the package public
#7 opened by TomDLT - 3
- 1
dual weights from `solve_kernel_ridge_eigenvalues` are incorrect when `n_samples < n_targets`
#22 opened by mvdoc - 2
split=True on model predictions for GroupRidgeCV does not return predictions for each input feature set?
#20 opened by sreejank - 0
AttributeError: 'ColumnKernelizer' object has no attribute 'force_cpu' when reloading a model
#18 opened by mvdoc - 0
Write more test for backends
#2 opened by TomDLT - 3
Implement Ridge regression
#1 opened by TomDLT - 1
do we still need preprocessed_fmri.json?
#10 opened by fatmai - 1
Add a documentation website
#6 opened by TomDLT - 1
- 0
Implement a Delayer
#5 opened by TomDLT