relNet - Modellierung von Themen und Strukturen religiöser Online-Kommunikation. - Frederik Elwert; Samira Tabti; Volkhard Krech; Katharina Morik; Lukas Pfahler (DHd, 2017)

Learning Low-Rank Document Embeddings with Weighted Nuclear Norm Regularization. - Lukas Pfahler; Katharina Morik; Frederik Elwert; Samira Tabti; Volkhard Krech (DSAA, 2017)

What do you do with 5 million posts? Versuche zum distant reading religiöser Online-Foren. - Lukas Pfahler; Frederik Elwert; Samira Tabti; Katharina Morik; Volker Krech (DHd, 2018)

Nyström-SGD: Fast Learning of Kernel-Classifiers with Conditioned Stochastic Gradient Descent. - Lukas Pfahler; Katharina Morik (ECML/PKDD (2), 2018)

The Search for Equations - Learning to Identify Similarities Between Mathematical Expressions. - Lukas Pfahler; Jonathan Schill; Katharina Morik (ECML/PKDD (3), 2019)

Interpretable Nearest Neighbor Queries for Tree-Structured Data in Vector Databases of Graph-Neural Network Embeddings. - Lukas Pfahler; Jan Richter (EDBT/ICDT Workshops, 2020)

Semantic Search in Millions of Equations. - Lukas Pfahler; Katharina Morik (KDD, 2020)

On-Site Gamma-Hadron Separation with Deep Learning on FPGAs. - Sebastian Buschjäger; Lukas Pfahler; Jens Buß; Katharina Morik; Wolfgang Rhode (ECML/PKDD (4), 2020)

Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2020)

Generalized Negative Correlation Learning for Deep Ensembling. - Sebastian Buschjäger; Lukas Pfahler; Katharina Morik (CoRR, 2020)

Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Christian Hakert; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (DATE, 2021)

Self-Supervised Source Code Annotation from Related Research Papers. - Pierre Haritz; Lukas Pfahler; Thomas Liebig; Helena Kotthaus (ICDM (Workshops), 2021)

Very Fast Streaming Submodular Function Maximization. - Sebastian Buschjäger; Philipp-Jan Honysz; Lukas Pfahler; Katharina Morik (ECML/PKDD (3), 2021)

Bit Error Tolerance Metrics for Binarized Neural Networks. - Sebastian Buschjäger; Jian-Jia Chen; Kuan-Hsun Chen; Mario Günzel; Katharina Morik; Rodion Novkin; Lukas Pfahler; Mikail Yayla (CoRR, 2021)

Noisy Labels for Weakly Supervised Gamma Hadron Classification. - Lukas Pfahler; Mirko Bunse; Katharina Morik (CoRR, 2021)

Explaining Deep Learning Representations by Tracing the Training Process. - Lukas Pfahler; Katharina Morik (CoRR, 2021)

Millions of Formulas. - Lukas Pfahler (Mach. Learn. under Resour. Constraints Vol. 1 (1), 2022)

Deep Learning Applications. - Wolfgang Rhode; Mirco Hünnefeld; Bernhard Spaan; Vukan Jevtic; Lukas Pfahler; Sebastian Buschjäger (Mach. Learn. under Resour. Constraints Vol. 2 (2), 2022)

Check Mate: A Sanity Check for Trustworthy AI. - Sascha Mücke; Lukas Pfahler (LWDA, 2022)

Self-Supervised Pretraining of Graph Neural Network for the Retrieval of Related Mathematical Expressions in Scientific Articles. - Lukas Pfahler; Katharina Morik (CoRR, 2022)

Some representation learning tasks and the inspection of their models. - Lukas Pfahler (2022)

Class-Conditional Label Noise in Astroparticle Physics. - Mirko Bunse; Lukas Pfahler (ECML/PKDD (6), 2023)

Exposing Bias in Online Communities through Large-Scale Language Models. - Celine Wald; Lukas Pfahler (CoRR, 2023)