tf_row_tensor

Row-wise tensor product using TensorFlow

Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as
proposed by Ruegamer et al. (2023) <doi:10.18637/jss.v105.i02>.
Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.

David Ruegamer

deepregression

Fitting Deep Distributional Regression

Christopher Marquardt

Laetitia Frost

Florian Pfisterer

Philipp Baumann

Chris Kolb

Lucas Kook

tf_row_tensor function

<dl><dt>a, b</dt>
<dd>tensor</dd>
<dt>...</dt>
<dd>arguments passed to TensorFlow layer</dd></dl>

Arguments

Row-wise tensor product using TensorFlow — tf_row_tensor

<dl>

<dt>a, b</dt>
<dd>tensor</dd>


<dt>...</dt>
<dd>arguments passed to TensorFlow layer</dd>

</dl>

tf_row_tensor: Row-wise tensor product using TensorFlow

Description

Usage

Value

Arguments