4 citations · 6 across the 3 of their papers we have counts for
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cs.LG2024★ 2 cited
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…
cs.LG2023★ 4 cited
Structural Neural Additive Models: Enhanced Interpretable Machine Learning
Mattias Luber, Anton Thielmann, Benjamin Säfken
Deep neural networks (DNNs) have shown exceptional performances in a wide range of tasks and have become the go-to method for problems requiring high-level predictive power. There…