T. Pevný
Adam L.
,
Mácha V.
,
Šmídl Václav
,
Pevný T.
:
General framework for binary classification on top samples
,
Optimization Methods & Software vol.37, 5 (2022), p. 1636-1667
[2022]
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DOI:
10.1080/10556788.2021.1965601
Škvára Vít
,
Šmídl Václav
,
Pevný T.
,
Seidl Jakub
,
Havránek Aleš
,
Tskhakaya David
:
Detection of Alfvén Eigenmodes on COMPASS with Generative Neural Networks
,
Fusion Science and Technology vol.76, 8 (2020), p. 962-971
[2020]
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DOI:
10.1080/15361055.2020.1820805
Šmídl Václav
,
Bím J.
,
Pevný T.
:
Orthogonal Approximation of Marginal Likelihood of Generative Models
,
Bayesian Deep Learning NeurIPS 2019 Workshop, 48
,
NeurIPS 2019, (Vancouver, CA, 20191208)
[2019]
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Flusser M.
,
Pevný T.
,
Somol Petr
:
Density-Approximating Neural Network Models for Anomaly Detection
,
ACM SIGKDD 2018 Workshop, p. 1-8
,
ACM SIGKDD 2018 Workshop, (London, GB, 20180820)
[2018]
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Pevný T.
,
Somol Petr
:
Discriminative models for multi-instance problems with tree-structure
,
Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security (AISec'16), p. 83-91
,
the 2016 ACM Workshop on Artificial Intelligence and Security (AISec'16), (Vienna, AT, 20161028)
[2016]
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DOI:
10.1145/2996758.2996761
Somol Petr
,
Pevný T.
:
Discriminative Models for Multi-instance Problems with Tree Structure
,
Proceedings of the 9th ACM Workshop on Artificial Intelligence and Security 2016
,
9th ACM Workshop on Artificial Intelligence and Security, (Vienna, AT, 28.10.2016)
[2016]
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DOI:
10.1145/2996758.2996761
Létal V.
,
Pevný T.
,
Šmídl Václav
,
Somol Petr
:
Finding New Malicious Domains Using Variational Bayes on Large-Scale Computer Network Data
,
NIPS Workshop: Advances in Approximate Bayesian Inference, p. 1-10
,
NIPS workshop: Advances in Approximate Bayesian Inference, (Montreal, CA, 11.12.2015)
[2015]
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