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Found 3 papers, 2 papers with code
Deep Dynamic Factor Models
A novel deep neural network framework -- that we refer to as Deep Dynamic Factor Model (D$^2$FM) --, is able to encode the information available, from hundreds of macroeconomic and financial time-series into a handful of unobserved latent states.
A Baseline for Shapley Values in MLPs: from Missingness to Neutrality
Deep neural networks have gained momentum based on their accuracy, but their interpretability is often criticised.
Explaining a prediction in some nonlinear models
In this article we will analyse how to compute the contribution of each input value to its aggregate output in some nonlinear models.
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