Julia Linhart

Could you give some more details about what you're having in mind for pre-configuered RNNs and CNNs?

The CNNEmbedding does not include Fully Connected Layers at the end right? successive layers with `conv2d - batchnorm - relu - maxpool` would be sufficient?

Cool! I have one for a CNN Embedding: ```python def build_2dcnn_layer( in_channels: int, out_channels: int, kernel_size: Tuple[int, ...], padding: Union[str, Tuple[int, ...]], ) -> nn.Sequential: """ Returns 2D convolutional layer...

For the RNN you can maybe put the input_size as an argument, as the Embedding net will be defined before the inference object: ```python rnn_embedding = RNNEmbedding(input_size=dict_size, num_layers=1, hidden_dims=16, out_features=disct_size)...

Hi @psteinb ! Sorry, I really didn't have the time to look at this PR for now! But I think it's great you took the time to look into and...

Thanks for this review! I'll do the changes, review the doc and fix typing issues.

Almost all the suggestions by @agramfort have been addressed. Except: - `pandas` is still used for the `.groupby()` method in the `marginal_plot_with_proba_intensity` function from `sbi.analysis.plot.py`. - the added simulator has...

I think I have addressed all your comments and requests @janfb, except the one where I should get rid of the `groupby` method from `pandas`. I will try to fix...

All done @janfb

Response to review from @janfb: the above commit fixes following requests - rename tutoral to `18_...`, plots and results description - change content of `anamysis/test_utils.py` to `sbi/utils/analysis_utils.py` - description of...