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Thomas Runkler

Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning


Jan 14, 2022
Phillip Swazinna, Steffen Udluft, Daniel Hein, Thomas Runkler

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* Submitted to IFAC Conference on Intelligent Control and Automation Sciences (ICONS)2022 
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Combining Sub-Symbolic and Symbolic Methods for Explainability


Dec 03, 2021
Anna Himmelhuber, Stephan Grimm, Sonja Zillner, Mitchell Joblin, Martin Ringsquandl, Thomas Runkler

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* RuleML+RR 2021 
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Measuring Data Quality for Dataset Selection in Offline Reinforcement Learning


Nov 26, 2021
Phillip Swazinna, Steffen Udluft, Thomas Runkler

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* Accepted at IEEE SSCI 2021 
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Ontology-Based Skill Description Learning for Flexible Production Systems


Nov 25, 2021
Anna Himmelhuber, Stephan Grimm, Thomas Runkler, Sonja Zillner

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* 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) 
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Demystifying Graph Neural Network Explanations


Nov 25, 2021
Anna Himmelhuber, Mitchell Joblin, Martin Ringsquandl, Thomas Runkler

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* [email protected]'21 
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Towards Data-Free Domain Generalization


Oct 25, 2021
Ahmed Frikha, Haokun Chen, Denis Krompaß, Thomas Runkler, Volker Tresp

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* Accepted at NeurIPS 2021 - DistShift Workshop 
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Learning through structure: towards deep neuromorphic knowledge graph embeddings


Sep 21, 2021
Victor Caceres Chian, Marcel Hildebrandt, Thomas Runkler, Dominik Dold

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* Accepted for publication at the International Conference on Neuromorphic Computing (ICNC 2021) 
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Behavior Constraining in Weight Space for Offline Reinforcement Learning


Jul 12, 2021
Phillip Swazinna, Steffen Udluft, Daniel Hein, Thomas Runkler

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* Accepted at ESANN 2021 
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The Synergy of Complex Event Processing and Tiny Machine Learning in Industrial IoT


May 04, 2021
Haoyu Ren, Darko Anicic, Thomas Runkler

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* Accepted by The 15th ACM International Conference on Distributed and Event-based Systems (DEBS) 2021 
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TinyOL: TinyML with Online-Learning on Microcontrollers


Apr 10, 2021
Haoyu Ren, Darko Anicic, Thomas Runkler

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* Accepted by The International Joint Conference on Neural Network (IJCNN) 2021 
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TopicBERT for Energy Efficient Document Classification


Oct 15, 2020
Yatin Chaudhary, Pankaj Gupta, Khushbu Saxena, Vivek Kulkarni, Thomas Runkler, Hinrich Schütze

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* EMNLP2020 (Findings): 9 pages, 5 figures, 8 Tables 
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Overcoming Model Bias for Robust Offline Deep Reinforcement Learning


Sep 09, 2020
Phillip Swazinna, Steffen Udluft, Thomas Runkler

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Neural Topic Modeling with Continual Lifelong Learning


Jun 19, 2020
Pankaj Gupta, Yatin Chaudhary, Thomas Runkler, Hinrich Schütze

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* ICML2020 
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Visual Evaluation of Generative Adversarial Networks for Time Series Data


Dec 23, 2019
Hiba Arnout, Johannes Kehrer, Johanna Bronner, Thomas Runkler

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* To appear in the Proceedings of the Human-Centered AI: Trustworthiness of AI Models & Data (HAI) track at AAAI Fall Symposium, DC, November 7-9, 2019 
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Lifelong Neural Topic Learning in Contextualized Autoregressive Topic Models of Language via Informative Transfers


Sep 29, 2019
Yatin Chaudhary, Pankaj Gupta, Thomas Runkler

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* 94 pages 
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Neural Architectures for Fine-Grained Propaganda Detection in News


Sep 13, 2019
Pankaj Gupta, Khushbu Saxena, Usama Yaseen, Thomas Runkler, Hinrich Schütze

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* EMNLP2019: Fine-grained propaganda detection shared task at NLP4IF workshop (EMNLP2019) 
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Interpretable Dynamics Models for Data-Efficient Reinforcement Learning


Jul 10, 2019
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek

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* ESANN 2019 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 24-26 April 2019, i6doc.com publ., ISBN 978-287-587-065-0 
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Multimodal Deep Gaussian Processes


Oct 16, 2018
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek

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Neural Relation Extraction Within and Across Sentence Boundaries


Oct 11, 2018
Pankaj Gupta, Subburam Rajaram, Hinrich Schütze, Bernt Andrassy, Thomas Runkler

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* #AAAI2019 under review 
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Bayesian Alignments of Warped Multi-Output Gaussian Processes


May 23, 2018
Markus Kaiser, Clemens Otte, Thomas Runkler, Carl Henrik Ek

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Sensitivity Analysis for Predictive Uncertainty in Bayesian Neural Networks


Dec 10, 2017
Stefan Depeweg, José Miguel Hernández-Lobato, Steffen Udluft, Thomas Runkler

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Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies


Aug 15, 2017
Daniel Hein, Alexander Hentschel, Thomas Runkler, Steffen Udluft

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* Engineering Applications of Artificial Intelligence, Volume 65C, October 2017, Pages 87-98 
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