On the spectrum between binary relevance and classifier chains in multi-label classification. - Sophie Burkhardt; Stefan Kramer 001 (SAC, 2015)

Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models. - Sophie Burkhardt; Stefan Kramer 001 (ECML/PKDD (2), 2017)

Online multi-label dependency topic models for text classification. - Sophie Burkhardt; Stefan Kramer 001 (Mach. Learn., 2018)

Online Multi-label Text Classification using Topic Models. - Sophie Burkhardt (2018)

Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model. - Sophie Burkhardt; Stefan Kramer 001 (J. Mach. Learn. Res., 2019)

Multi-label classification using stacked hierarchical Dirichlet processes with reduced sampling complexity. - Sophie Burkhardt; Stefan Kramer 001 (Knowl. Inf. Syst., 2019)

A Survey of Multi-Label Topic Models. - Sophie Burkhardt; Stefan Kramer 001 (SIGKDD Explor., 2019)

Towards Identifying Drug Side Effects from Social Media Using Active Learning andCrowd Sourcing. - Sophie Burkhardt; Julia Siekiera; Josua Glodde; Miguel A. Andrade-Navarro; Stefan Kramer 001 (PSB, 2020)

Topic-Guided Knowledge Graph Construction for Argument Mining. - Weichen Li; Patrick Abels; Zahra Ahmadi; Sophie Burkhardt; Benjamin Schiller; Iryna Gurevych; Stefan Kramer 001 (ICBK, 2021)

Focusing Knowledge-based Graph Argument Mining via Topic Modeling. - Patrick Abels; Zahra Ahmadi; Sophie Burkhardt; Benjamin Schiller; Iryna Gurevych; Stefan Kramer 001 (CoRR, 2021)

Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation. - Sophie Burkhardt; Jannis Brugger; Nicolas Wagner 001; Zahra Ahmadi; Kristian Kersting; Stefan Kramer 001 (Frontiers Artif. Intell., 2021)

A Call for Standardization and Validation of Text Style Transfer Evaluation. - Phil Ostheimer; Mayank Kumar Nagda; Marius Kloft; Sophie Fellenz (ACL (Findings), 2023)

Constraint-Based Parameterization and Disentanglement of Aerodynamic Shapes Using Deep Generative Models. - Asmita Bhat; Nooshin HajiGhassemi; Deepak Nagaraj; Sophie Fellenz (ECML/PKDD (6), 2023)

Ordinal Regression for Difficulty Prediction of StepMania Levels. - Billy Joe Franks; Benjamin Dinkelmann; Marius Kloft; Sophie Fellenz (ECML/PKDD (6), 2023)

Learning to Play Text-Based Adventure Games with Maximum Entropy Reinforcement Learning. - Weichen Li; Rati Devidze; Sophie Fellenz (ECML/PKDD (4), 2023)

Ordinal Regression for Difficulty Estimation of StepMania Levels. - Billy Joe Franks; Benjamin Dinkelmann; Sophie Fellenz; Marius Kloft (CoRR, 2023)

Potential-based reward shaping for learning to play text-based adventure games. - Weichen Li; Rati Devidze; Sophie Fellenz (CoRR, 2023)

Deep Anomaly Detection on Tennessee Eastman Process Data. - Fabian Hartung; Billy Joe Franks; Tobias Michels; Dennis Wagner; Philipp Liznerski; Steffen Reithermann; Sophie Fellenz; Fabian Jirasek; Maja Rudolph; Daniel Neider; Heike Leitte; Chen Song; et al. (CoRR, 2023)

Evaluating Dynamic Topic Models. - Charu James; Mayank Nagda; Nooshin Haji Ghassemi; Marius Kloft; Sophie Fellenz (ACL (1), 2024)

Ethics in Action: Training Reinforcement Learning Agents for Moral Decision-making In Text-based Adventure Games. - Weichen Li; Rati Devidze; Waleed Mustafa; Sophie Fellenz (AISTATS, 2024)

Text Style Transfer Evaluation Using Large Language Models. - Phil Sidney Ostheimer; Mayank Kumar Nagda; Marius Kloft; Sophie Fellenz (LREC/COLING, 2024)

Characterizing Text Datasets with Psycholinguistic Features. - Marcio Monteiro; Charu Karakkaparambil James; Marius Kloft; Sophie Fellenz (EMNLP (Findings), 2024)

Putting Back the Stops: Integrating Syntax with Neural Topic Models. - Mayank Nagda; Sophie Fellenz (IJCAI, 2024)

Reimagining Anomalies: What If Anomalies Were Normal? - Philipp Liznerski; Saurabh Varshneya; Ece Calikus; Sophie Fellenz; Marius Kloft (CoRR, 2024)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; Christoph Lippert; et al. (CoRR, 2024)

HANNA: Hard-constraint Neural Network for Consistent Activity Coefficient Prediction. - Thomas Specht; Mayank Nagda; Sophie Fellenz; Stephan Mandt; Hans Hasse; Fabian Jirasek (CoRR, 2024)

Comgra: A Tool for Analyzing and Debugging Neural Networks. - Florian Dietz; Sophie Fellenz; Dietrich Klakow; Marius Kloft (CoRR, 2024)

SetPINNs: Set-based Physics-informed Neural Networks. - Mayank Nagda; Phil Ostheimer; Thomas Specht; Frank Rhein; Fabian Jirasek; Marius Kloft; Sophie Fellenz (CoRR, 2024)

KnowTD─An Actionable Knowledge Representation System for Thermodynamics. - Luisa Vollmer; Sophie Fellenz; Fabian Jirasek; Heike Leitte; Hans Hasse (J. Chem. Inf. Model., 2024)

BBPOS: BERT-based Part-of-Speech Tagging for Uzbek. - Latofat Bobojonova; Arofat Akhundjanova; Phil Sidney Ostheimer; Sophie Fellenz (COLING Workshops, 2025)

Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors. - Mayank Nagda; Phil Ostheimer; Sophie Fellenz (NAACL (Findings), 2025)

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. - Billy Joe Franks; Moshe Eliasof; Semih Cantürk; Guy Wolf; Carola-Bibiane Schönlieb; Sophie Fellenz; Marius Kloft (Trans. Mach. Learn. Res., 2025)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Clara Meister; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; et al. (Trans. Mach. Learn. Res., 2025)

Challenging Assumptions in Learning Generic Text Style Embeddings. - Phil Ostheimer; Marius Kloft; Sophie Fellenz (CoRR, 2025)

Multi-level Supervised Contrastive Learning. - Naghmeh Ghanooni; Barbod Pajoum; Harshit Rawal; Sophie Fellenz; Vo Nguyen Le Duy; Marius Kloft (CoRR, 2025)

Sparse Data Generation Using Diffusion Models. - Phil Ostheimer; Mayank Nagda; Marius Kloft; Sophie Fellenz (CoRR, 2025)

Using Large Language Models for Solving Thermodynamic Problems. - Rebecca Loubet; Pascal Zittlau; Luisa Vollmer; Marco Hoffmann; Sophie Fellenz; Fabian Jirasek; Heike Leitte; Hans Hasse (CoRR, 2025)

Superstudent intelligence in thermodynamics. - Rebecca Loubet; Pascal Zittlau; Marco Hoffmann; Luisa Vollmer; Sophie Fellenz; Heike Leitte; Fabian Jirasek; Johannes Lenhard; Hans Hasse (CoRR, 2025)

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems. - Jan Tauberschmidt; Sophie Fellenz; Sebastian J. Vollmer; Andrew B. Duncan (CoRR, 2025)

Continual Neural Topic Model. - Charu Karakkaparambil James; Waleed Mustafa; Marius Kloft; Sophie Fellenz (CoRR, 2025)