3 citations · 5 across the 3 of their papers we have counts for
3 papers
A Machine Learning and Explainable AI Framework Tailored for Unbalanced Experimental Catalyst Discovery
Parastoo Semnani, Mihail Bogojeski, Florian Bley +7
The successful application of machine learning (ML) in catalyst design relies on high-quality and diverse data to ensure effective generalization to novel compositions, thereby aid…
Probabilistic Topic Modelling with Transformer Representations
Arik Reuter, Anton Thielmann, Christoph Weisser +2
Topic modelling was mostly dominated by Bayesian graphical models during the last decade. With the rise of transformers in Natural Language Processing, however, several successful…
Twitmo: A Twitter Data Topic Modeling and Visualization Package for R
Andreas Buchmüller, Gillian Kant, Christoph Weisser +3
We present Twitmo, a package that provides a broad range of methods to collect, pre-process, analyze and visualize geo-tagged Twitter data. Twitmo enables the user to collect geo-t…