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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 SchĂĽtze

* 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

* 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

* 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 SchĂĽtze

* 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

* 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 SchĂĽtze, Bernt Andrassy, Thomas Runkler

* #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

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

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