4 papers
From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning
Manish Kumar, Anton Frederik Thielmann, Christoph Weisser +2
Numerical preprocessing remains a critical component of tabular deep learning, as the representation of continuous features can strongly affect downstream performance. We systemati…
GPTopic: Dynamic and Interactive Topic Representations
Arik Reuter, Bishnu Khadka, Anton Thielmann +3
Topic modeling seems to be almost synonymous with generating lists of top words to represent topics within large text corpora. However, deducing a topic from such list of individua…
Mambular: A Sequential Model for Tabular Deep Learning
Anton Frederik Thielmann, Manish Kumar, Christoph Weisser +3
The analysis of tabular data has traditionally been dominated by gradient-boosted decision trees (GBDTs), known for their proficiency with mixed categorical and numerical features.…
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…