research
∙
03/30/2023
Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence
Extracting and identifying latent topics in large text corpora has gaine...
share
research
∙
02/18/2023
Structural Neural Additive Models: Enhanced Interpretable Machine Learning
Deep neural networks (DNNs) have shown exceptional performances in a wid...
research
∙
01/27/2023
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
Deep neural networks (DNNs) have proven to be highly effective in a vari...
research
∙
12/19/2022
Human in the loop: How to effectively create coherent topics by manually labeling only a few documents per class
Few-shot methods for accurate modeling under sparse label-settings have ...
research
∙
07/08/2022
Twitmo: A Twitter Data Topic Modeling and Visualization Package for R
We present Twitmo, a package that provides a broad range of methods to c...
research
∙
11/02/2020
Gradient Boosting for Linear Mixed Models
Gradient boosting from the field of statistical learning is widely known...
research
∙
03/15/2018