Sophie Fellenz

According to our database, Sophie Fellenz authored at least 22 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

CoRR, 2024

Reimagining Anomalies: What If Anomalies Were Normal?

Philipp Liznerski, Saurabh Varshneya, Ece Calikus, Sophie Fellenz, Marius Kloft

CoRR, 2024

2023

Evaluating Dynamic Topic Models.

Charu James, Mayank Nagda, Nooshin Haji Ghassemi, Marius Kloft, Sophie Fellenz

CoRR, 2023

Text Style Transfer Evaluation Using Large Language Models.

Phil Ostheimer, Mayank Nagda, Marius Kloft, 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, Benjamin Klöpper, Stephan Mandt, Michael Bortz, Jakob Burger, Hans Hasse, Marius Kloft

CoRR, 2023

Potential-based reward shaping for learning to play text-based adventure games.

Weichen Li, Rati Devidze, Sophie Fellenz

CoRR, 2023

Ordinal Regression for Difficulty Estimation of StepMania Levels.

Billy Joe Franks, Benjamin Dinkelmann, Sophie Fellenz, Marius Kloft

CoRR, 2023

Learning to Play Text-Based Adventure Games with Maximum Entropy Reinforcement Learning.

Weichen Li, Rati Devidze, Sophie Fellenz

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Ordinal Regression for Difficulty Prediction of StepMania Levels.

Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

Constraint-Based Parameterization and Disentanglement of Aerodynamic Shapes Using Deep Generative Models.

Asmita Bhat, Nooshin HajiGhassemi, Deepak Nagaraj, Sophie Fellenz

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

A Call for Standardization and Validation of Text Style Transfer Evaluation.

Phil Ostheimer, Mayank Kumar Nagda, Marius Kloft, Sophie Fellenz

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2021

Rule Extraction From Binary Neural Networks With Convolutional Rules for Model Validation.

Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer

Frontiers Artif. Intell., 2021

Focusing Knowledge-based Graph Argument Mining via Topic Modeling.

Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer

CoRR, 2021

Topic-Guided Knowledge Graph Construction for Argument Mining.

Weichen Li, Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer

Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

2020

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

Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

2019

A Survey of Multi-Label Topic Models.

Sophie Burkhardt, Stefan Kramer

SIGKDD Explor., 2019

Multi-label classification using stacked hierarchical Dirichlet processes with reduced sampling complexity.

Sophie Burkhardt, Stefan Kramer

Knowl. Inf. Syst., 2019

Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model.

Sophie Burkhardt, Stefan Kramer

J. Mach. Learn. Res., 2019

2018

Online Multi-label Text Classification using Topic Models.

Sophie Burkhardt

PhD thesis, 2018

Online multi-label dependency topic models for text classification.

Sophie Burkhardt, Stefan Kramer

Mach. Learn., 2018

2017

Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models.

Sophie Burkhardt, Stefan Kramer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2015

On the spectrum between binary relevance and classifier chains in multi-label classification.

Sophie Burkhardt, Stefan Kramer

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015