Community-Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models. - Mattias Luber; Anton Thielmann; Christoph Weisser; Benjamin Säfken (CoRR, 2021)

AuDoLab: Automatic document labelling and classification for extremely unbalanced data. - Arne Tillmann; Anton Thielmann; Gillian Kant; Christoph Weisser; Benjamin Säfken; Alexander Silbersdorff; Thomas Kneib (J. Open Source Softw., 2021)

Coherence based Document Clustering. - Anton Thielmann; Christoph Weisser; Thomas Kneib; Benjamin Säfken (ICSC, 2023)

Structural Neural Additive Models: Enhanced Interpretable Machine Learning. - Mattias Luber; Anton Thielmann; Benjamin Säfken (CoRR, 2023)

Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence. - Anton Thielmann; Quentin Seifert; Arik Reuter; Elisabeth Bergherr; Benjamin Säfken (CoRR, 2023)

Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data. - Christoph Weisser; Christoph Gerloff; Anton Thielmann; Andre Python; Arik Reuter; Thomas Kneib; Benjamin Säfken (Comput. Stat., 2023)

STREAM: Simplified Topic Retrieval, Exploration, and Analysis Module. - Anton Thielmann; Arik Reuter; Christoph Weisser; Gillian Kant; Manish Kumar; Benjamin Säfken (ACL (Short Papers), 2024)

Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean. - Anton Frederik Thielmann; René-Marcel Kruse; Thomas Kneib; Benjamin Säfken (AISTATS, 2024)

Human in the Loop: How to Effectively Create Coherent Topics by Manually Labeling Only a Few Documents per Class. - Anton Frederik Thielmann; Christoph Weisser; Benjamin Säfken (LREC/COLING, 2024)

On the Efficiency of NLP-Inspired Methods for Tabular Deep Learning. - Anton Frederik Thielmann; Soheila Samiee (ENLSP, 2024)

Topics in the Haystack: Enhancing Topic Quality through Corpus Expansion. - Anton Thielmann; Arik Reuter; Quentin Seifert; Elisabeth Bergherr; Benjamin Säfken (Comput. Linguistics, 2024)

GPTopic: Dynamic and Interactive Topic Representations. - Arik Reuter; Anton Thielmann; Christoph Weisser; Sebastian Fischer 004; Benjamin Säfken (CoRR, 2024)

Probabilistic Topic Modelling with Transformer Representations. - Arik Reuter; Anton Thielmann; Christoph Weisser; Benjamin Säfken; Thomas Kneib (CoRR, 2024)

Neural Additive Image Model: Interpretation through Interpolation. - Arik Reuter; Anton Thielmann; Benjamin Säfken (CoRR, 2024)

Mambular: A Sequential Model for Tabular Deep Learning. - Anton Frederik Thielmann; Manish Kumar; Christoph Weisser; Arik Reuter; Benjamin Säfken; Soheila Samiee (CoRR, 2024)

Interpretable Additive Tabular Transformer Networks. - Anton Frederik Thielmann; Arik Reuter; Thomas Kneib; David Rügamer; Benjamin Säfken (Trans. Mach. Learn. Res., 2024)

One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading. - Gillian Kant; Ivan Zhelyazkov; Anton Thielmann; Christoph Weisser; Michael Schlee; Christoph Ehrling; Benjamin Säfken; Thomas Kneib (Soc. Netw. Anal. Min., 2024)

Beyond Black-Box Predictions: Identifying Marginal Feature Effects in Tabular Transformer Networks. - Anton Thielmann; Arik Reuter; Benjamin Säfken (CoRR, 2025)

Gradient-based smoothing parameter estimation for neural P-splines. - Lea M. Dammann; Marei Freitag; Anton Thielmann; Benjamin Säfken (Comput. Stat., 2025)