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Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks


Apr 19, 2021
Šimon Mandlík, Tomáš Pevný

* Master thesis, 108 page, 56 figures 

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Comparison of Anomaly Detectors: Context Matters


Dec 18, 2020
Vít Škvára, Jan Franců, Matěj Zorek, Tomáš Pevný, Václav Šmídl


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Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks


Sep 25, 2020
Jaromír Janisch, Tomáš Pevný, Viliam Lisý


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Neural Power Units


Jun 05, 2020
Niklas Heim, Tomáš Pevný, Václav Šmídl


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General Framework for Binary Classification on Top Samples


Feb 25, 2020
Lukáš Adam, Václav Mácha, Václav Šmídl, Tomáš Pevný


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Rodent: Relevance determination in ODE


Dec 02, 2019
Niklas Heim, Václav Šmídl, Tomáš Pevný


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Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces


Nov 20, 2019
Jaromír Janisch, Tomáš Pevný, Viliam Lisý


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Classification with Costly Features as a Sequential Decision-Making Problem


Sep 05, 2019
Jaromír Janisch, Tomáš Pevný, Viliam Lisý


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Anomaly scores for generative models


May 28, 2019
Václav Šmídl, Jan Bím, Tomáš Pevný

* 9 pages, 3 figures, submitted to NeurIPS 2019 

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Are generative deep models for novelty detection truly better?


Jul 13, 2018
Vít Škvára, Tomáš Pevný, Václav Šmídl

* 7 pages, ODD v5.0 - KDD 2018 workshop 

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Classification with Costly Features using Deep Reinforcement Learning


Nov 20, 2017
Jaromír Janisch, Tomáš Pevný, Viliam Lisý


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