Thomas Robinson

Hi @GuillemGSubies, thanks for raising this issue! Support for 3.9 should be implemented soon, we just need to check the tensorflow dependencies. Tom

Thanks for bringing this to our attention. We agree that it would be great to have support for the scikit-learn interface, and so we do plan to support this in...

Hi @mabdelhack -- you can impute data after training the model using the `.generate_samples()` function which saves m imputed datasets to the .output_list attribute. If you are referring to entirely...

Hi @muhammad92syahrul and @mabdelhack! We still don't have a specific function for your purposes, but I wanted to flag the `.change_imputation_target()` method (found [here](https://github.com/MIDASverse/MIDASpy/blob/213eb854801570fa0cfe422c856b2925dd1f8dfe/MIDASpy/midas_base.py#L1780) in the source code). This method...

Hi @neuro30, thanks for sharing this. Multi-GPU support is not currently available for MIDASpy unfortunately. You should be able to get single-GPU support working if CUDA is properly configured for...

Thanks @ThirstyGeo for raising this issue -- completely agree that it would be a really useful feature. The best way to implement this is probably to allow users to change...

Hi @ThirstyGeo, thanks for sharing this test. It's very interesting, and I agree it would be good if the MIDAS model could somehow account for this type of dependence between...

Hi @aeggers, are you using an Apple Silicon Mac by any chance?

Sorry for the slow reply @aeggers! We are working on a general fix to this issue, which should be released soon. In the meantime, we would recommend using [miniforge](https://github.com/conda-forge/miniforge) to...

Hi @vincentheddesheimer -- I think the issue here is you are still using the x86 installer rather than the Apple Silicon native installer for your M2 Macbook (https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh) You may...