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This issue is only about setting up models and training, evaluation of such models will be handled in a separate issue. Thus, it is mainly about writing the TensorModel abstraction and some implementations of it.
The goal is to enable training of autoencoders, prediction of 2-dimensional tensors for geospatial analysis and so on.
I am not entirely sure how to deal with models that take multi-dim data and predict scalars like CNN-based classifiers and regressors (a very common use case). VectorModel does not feel like the right fit, nor does TensorModel (because it will focus on tensor-like prediction). @opcode81 Do you have an idea about that?
The text was updated successfully, but these errors were encountered:
This issue is only about setting up models and training, evaluation of such models will be handled in a separate issue. Thus, it is mainly about writing the TensorModel abstraction and some implementations of it.
The goal is to enable training of autoencoders, prediction of 2-dimensional tensors for geospatial analysis and so on.
I am not entirely sure how to deal with models that take multi-dim data and predict scalars like CNN-based classifiers and regressors (a very common use case). VectorModel does not feel like the right fit, nor does TensorModel (because it will focus on tensor-like prediction). @opcode81 Do you have an idea about that?
The text was updated successfully, but these errors were encountered: