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ORCIDTomás Pevný
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- affiliation: Czech Technical University in Prague, Czech Republic
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Journal Articles
- 2024
[j26]Jaromír Janisch
, Tomás Pevný, Viliam Lisý:
Classification with costly features in hierarchical deep sets. Mach. Learn. 113(7): 4487-4522 (2024)- [j25]Vít Skvára, Václav Smídl, Tomás Pevný:
Anomaly detection in multifactor data. Neural Comput. Appl. 36(34): 21561-21580 (2024) - [j24]Michaela Masková, Matej Zorek, Tomás Pevný, Václav Smídl:
Deep anomaly detection on set data: Survey and comparison. Pattern Recognit. 151: 110381 (2024) - [j23]Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer:
Malicious Internet Entity Detection Using Local Graph Inference. IEEE Trans. Inf. Forensics Secur. 19: 3554-3566 (2024) - [j22]Florian Merkle, Maximilian Samsinger, Pascal Schöttle, Tomás Pevný:
On the Economics of Adversarial Machine Learning. IEEE Trans. Inf. Forensics Secur. 19: 4670-4685 (2024) - 2023
- [j21]Quentin Giboulot, Tomás Pevný, Andrew D. Ker:
The Non-Zero-Sum Game of Steganography in Heterogeneous Environments. IEEE Trans. Inf. Forensics Secur. 18: 4436-4448 (2023) - 2022
- [j20]Simon Mandlík, Matej Racinsky, Viliam Lisý, Tomás Pevný:
JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data. J. Mach. Learn. Res. 23: 298:1-298:5 (2022) - [j19]Lukás Adam, Václav Mácha, Václav Smídl, Tomás Pevný:
General framework for binary classification on top samples. Optim. Methods Softw. 37(5): 1636-1667 (2022) - [j18]Solène Bernard, Patrick Bas, John Klein, Tomás Pevný:
Backpack: A Backpropagable Adversarial Embedding Scheme. IEEE Trans. Inf. Forensics Secur. 17: 3539-3554 (2022) - [j17]Vít Skvára, Jan Francu, Matej Zorek, Tomás Pevný, Václav Smídl:
Comparison of Anomaly Detectors: Context Matters. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2494-2507 (2022) - 2021
- [j16]Solène Bernard, Patrick Bas, John Klein, Tomás Pevný:
Explicit Optimization of min max Steganographic Game. IEEE Trans. Inf. Forensics Secur. 16: 812-823 (2021) - 2020
- [j15]Martin Kopp, Tomás Pevný, Martin Holena:
Anomaly explanation with random forests. Expert Syst. Appl. 149: 113187 (2020) - [j14]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with costly features as a sequential decision-making problem. Mach. Learn. 109(8): 1587-1615 (2020) - 2019
- [j13]Paul Prasse, René Knaebel, Lukás Machlica, Tomás Pevný, Tobias Scheffer:
Joint detection of malicious domains and infected clients. Mach. Learn. 108(8-9): 1353-1368 (2019) - 2018
- [j12]Jan Stiborek, Tomás Pevný, Martin Rehák:
Probabilistic analysis of dynamic malware traces. Comput. Secur. 74: 221-239 (2018) - [j11]Jan Stiborek, Tomás Pevný, Martin Rehák:
Multiple instance learning for malware classification. Expert Syst. Appl. 93: 346-357 (2018) - [j10]Jan Kohout, Tomás Pevný:
Network Traffic Fingerprinting Based on Approximated Kernel Two-Sample Test. IEEE Trans. Inf. Forensics Secur. 13(3): 788-801 (2018) - 2017
- [j9]Martin Grill, Tomás Pevný, Martin Rehák:
Reducing false positives of network anomaly detection by local adaptive multivariate smoothing. J. Comput. Syst. Sci. 83(1): 43-57 (2017) - 2016
- [j8]Martin Grill, Tomás Pevný:
Learning combination of anomaly detectors for security domain. Comput. Networks 107: 55-63 (2016) - [j7]Jan Jusko, Martin Rehák, Jan Stiborek, Jan Kohout, Tomás Pevný:
Using Behavioral Similarity for Botnet Command-and-Control Discovery. IEEE Intell. Syst. 31(5): 16-22 (2016) - [j6]Tomás Pevný:
Loda: Lightweight on-line detector of anomalies. Mach. Learn. 102(2): 275-304 (2016) - 2014
- [j5]Andrew D. Ker, Tomás Pevný:
The Steganographer is the Outlier: Realistic Large-Scale Steganalysis. IEEE Trans. Inf. Forensics Secur. 9(9): 1424-1435 (2014) - 2012
- [j4]Tomás Pevný, Jessica J. Fridrich, Andrew D. Ker:
From Blind to Quantitative Steganalysis. IEEE Trans. Inf. Forensics Secur. 7(2): 445-454 (2012) - 2010
- [j3]Tomás Pevný, Patrick Bas, Jessica J. Fridrich:
Steganalysis by subtractive pixel adjacency matrix. IEEE Trans. Inf. Forensics Secur. 5(2): 215-224 (2010) - 2008
- [j2]Tomás Pevný, Jessica J. Fridrich:
Detection of Double-Compression in JPEG Images for Applications in Steganography. IEEE Trans. Inf. Forensics Secur. 3(2): 247-258 (2008) - [j1]Tomás Pevný, Jessica J. Fridrich:
Multiclass Detector of Current Steganographic Methods for JPEG Format. IEEE Trans. Inf. Forensics Secur. 3(4): 635-650 (2008)
Conference and Workshop Papers
- 2026
- [c65]Armin Hadzic, Milan Papez, Tomás Pevný:
Distillation of a tractable model from the VQ-VAE. ESANN 2026 - [c64]Matej Zorek, Tomás Pevný, Rainer Böhme:
Agility for Steganalysis: Dealing with Distribution Drift in JPEG File Structures. EuroS&P 2026: 1313-1325 - [c63]Jan Francu, Milan Papez, Tomás Pevný:
Cover-Source Mismatch in Deepfake Detection: A Systematic Study. IH&MMSec 2026: 28-39 - [c62]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Tackle CSM in JPEG Steganalysis with Data Adaptation. IH&MMSec 2026: 121-126 - [c61]Aurélien Noirault, Tomás Pevný, Jan Butora, Vincent Itier, Patrick Bas:
Better Inversion of Diffusion Models for Generative Steganography. IH&MMSec 2026: 127-137 - 2025
- [c60]Rostislav Horcík, Gustav Sír, Vítezslav Simek, Tomás Pevný:
State Encodings for GNN-Based Lifted Planners. AAAI 2025: 26525-26533 - [c59]Matej Zorek, Tomás Pevný, Václav Smídl:
Differentiable Distance Between Hierarchically-Structured Data. ICDM 2025: 1751-1760 - [c58]Jiri Nemecek, Tomás Pevný, Jakub Marecek:
Generating Likely Counterfactuals Using Sum-Product Networks. ICLR 2025 - [c57]Jiri Nemecek, Mark Kozdoba, Illia Kryvoviaz, Tomás Pevný, Jakub Marecek:
Bias Detection via Maximum Subgroup Discrepancy. KDD (2) 2025: 2174-2185 - [c56]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs. UAI 2025: 3416-3450 - 2024
- [c55]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs. ICLR 2024 - 2023
- [c54]Leah Chrestien, Tomás Pevný, Stefan Edelkamp, Antonín Komenda:
Heuristic Search Optimisation Using Planning and Curriculum Learning Techniques. EPIA (1) 2023: 495-507 - [c53]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios. ESORICS Workshops (2) 2023: 589-608 - [c52]Leah Chrestien, Stefan Edelkamp, Antonín Komenda, Tomás Pevný:
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal. NeurIPS 2023 - [c51]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Leveraging Data Geometry to Mitigate CSM in Steganalysis. WIFS 2023: 1-6 - 2022
- [c50]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Using Set Covering to Generate Databases for Holistic Steganalysis. WIFS 2022: 1-6 - 2021
- [c49]Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomás Pevný:
When Should You Defend Your Classifier? - - A Game-Theoretical Analysis of Countermeasures Against Adversarial Examples. GameSec 2021: 158-177 - [c48]Solène Bernard, Patrick Bas, Tomás Pevný, John Klein:
Optimizing Additive Approximations of Non-additive Distortion Functions. IH&MMSec 2021: 105-112 - 2020
- [c47]Marek Dedic, Tomás Pevný, Lukás Bajer, Martin Holena:
Loss Functions for Clustering in Multi-instance Learning. ITAT 2020: 137-146 - [c46]Niklas Heim, Tomás Pevný, Václav Smídl:
Neural Power Units. NeurIPS 2020 - [c45]Tomás Pevný, Václav Smídl, Martin Trapp, Ondrej Polácek, Tomás Oberhuber:
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations. PGM 2020: 341-352 - 2019
- [c44]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features Using Deep Reinforcement Learning. AAAI 2019: 3959-3966 - [c43]Solène Bernard, Tomás Pevný, Patrick Bas, John Klein:
Exploiting Adversarial Embeddings for Better Steganography. IH&MMSec 2019: 216-221 - 2018
- [c42]Tomás Pevný, Andrew D. Ker:
Exploring Non-Additive Distortion in Steganography. IH&MMSec 2018: 109-114 - 2017
- [c41]Karel Durkota, Viliam Lisý, Christopher Kiekintveld, Karel Horák, Branislav Bosanský, Tomás Pevný:
Optimal Strategies for Detecting Data Exfiltration by Internal and External Attackers. GameSec 2017: 171-192 - [c40]Tomás Pevný, Petr Somol:
Using Neural Network Formalism to Solve Multiple-Instance Problems. ISNN (1) 2017: 135-142 - [c39]Paul Prasse, Lukás Machlica, Tomás Pevný, Jirí Havelka, Tobias Scheffer:
Malware Detection by Analysing Encrypted Network Traffic with Neural Networks. ECML/PKDD (2) 2017: 73-88 - [c38]Jakub Lokoc, Tomás Grosup, Premysl Cech, Tomás Pevný, Tomás Skopal:
Malware Discovery Using Behaviour-Based Exploration of Network Traffic. SISAP 2017: 315-323 - [c37]Paul Prasse, Lukás Machlica, Tomás Pevný, Jirí Havelka, Tobias Scheffer:
Malware Detection by Analysing Network Traffic with Neural Networks. IEEE Symposium on Security and Privacy Workshops 2017: 205-210 - 2016
- [c36]Tomás Pevný, Petr Somol:
Discriminative Models for Multi-instance Problems with Tree Structure. AISec@CCS 2016: 83-91 - [c35]Andrew D. Ker, Tomás Pevný, Patrick Bas:
Rethinking Optimal Embedding. IH&MMSec 2016: 93-102 - [c34]Tomás Pevný, Martin Kopp, Jakub Kroustek, Andrew D. Ker:
Malicons: Detecting Payload in Favicons. Media Watermarking, Security, and Forensics 2016: 1-9 - [c33]Jakub Lokoc, Jan Kohout, Premysl Cech, Tomás Skopal, Tomás Pevný:
k-NN Classification of Malware in HTTPS Traffic Using the Metric Space Approach. PAISI 2016: 131-145 - [c32]Premysl Cech, Jan Kohout, Jakub Lokoc, Tomás Komárek, Jakub Marousek, Tomás Pevný:
Feature Extraction and Malware Detection on Large HTTPS Data Using MapReduce. SISAP 2016: 311-324 - [c31]Tomás Komárek, Martin Grill, Tomás Pevný:
Passive NAT detection using HTTP access logs. WIFS 2016: 1-6 - 2015
- [c30]Jan Kohout, Tomás Pevný:
Unsupervised detection of malware in persistent web traffic. ICASSP 2015: 1757-1761 - [c29]Jan Kohout, Tomás Pevný:
Automatic discovery of web servers hosting similar applications. IM 2015: 1310-1315 - [c28]Tomás Pevný, Andrew D. Ker:
Towards dependable steganalysis. Media Watermarking, Security, and Forensics 2015: 94090I - [c27]Rémi Cogranne, Vahid Sedighi, Jessica J. Fridrich, Tomás Pevný:
Is ensemble classifier needed for steganalysis in high-dimensional feature spaces? WIFS 2015: 1-6 - [c26]Tomás Pevný, Ivan Nikolaev:
Optimizing pooling function for pooled steganalysis. WIFS 2015: 1-6 - 2014
- [c25]Tomás Pevný, Andrew D. Ker:
Steganographic key leakage through payload metadata. IH&MMSec 2014: 109-114 - [c24]Andrew D. Ker, Tomás Pevný:
A mishmash of methods for mitigating the model mismatch mess. Media Watermarking, Security, and Forensics 2014: 90280I - [c23]Viliam Lisý, Robert Kessl, Tomás Pevný:
Randomized Operating Point Selection in Adversarial Classification. ECML/PKDD (2) 2014: 240-255 - 2013
- [c22]Tomás Pevný, Martin Komon, Martin Rehák:
Attacking the IDS learning processes. ICASSP 2013: 8687-8691 - [c21]Andrew D. Ker, Patrick Bas, Rainer Böhme, Rémi Cogranne, Scott Craver, Tomás Filler, Jessica J. Fridrich, Tomás Pevný:
Moving steganography and steganalysis from the laboratory into the real world. IH&MMSec 2013: 45-58 - [c20]Tomás Pevný, Andrew D. Ker:
The challenges of rich features in universal steganalysis. Media Watermarking, Security, and Forensics 2013: 86650M - 2012
- [c19]Andrew D. Ker, Tomás Pevný:
Identifying a steganographer in realistic and heterogeneous data sets. Media Watermarking, Security, and Forensics 2012: 83030N - [c18]Tomás Pevný:
Co-occurrence steganalysis in high dimensions. Media Watermarking, Security, and Forensics 2012: 83030B - [c17]Andrew David Ker, Tomás Pevný:
Batch steganography in the real world. MM&Sec 2012: 1-10 - [c16]Tomás Pevný, Martin Rehák, Martin Grill:
Detecting anomalous network hosts by means of PCA. WIFS 2012: 103-108 - 2011
- [c15]Patrick Bas, Tomás Filler, Tomás Pevný:
"Break Our Steganographic System": The Ins and Outs of Organizing BOSS. Information Hiding 2011: 59-70 - [c14]Andrew D. Ker, Tomás Pevný:
A new paradigm for steganalysis via clustering. Media Forensics and Security 2011: 78800U - [c13]Tomás Pevný:
Detecting messages of unknown length. Media Forensics and Security 2011: 78800T - 2010
- [c12]Tomás Pevný, Tomás Filler, Patrick Bas:
Using High-Dimensional Image Models to Perform Highly Undetectable Steganography. Information Hiding 2010: 161-177 - [c11]Jan Kodovský, Tomás Pevný, Jessica J. Fridrich:
Modern steganalysis can detect YASS. Media Forensics and Security 2010: 754102 - 2009
- [c10]Tomás Pevný, Jessica J. Fridrich, Andrew D. Ker:
From blind to quantitative steganalysis. Media Forensics and Security 2009: 72540C - [c9]Tomás Pevný, Patrick Bas, Jessica J. Fridrich:
Steganalysis by subtractive pixel adjacency matrix. MM&Sec 2009: 75-84 - 2008
- [c8]Tomás Pevný, Jessica J. Fridrich:
Benchmarking for Steganography. Information Hiding 2008: 251-267 - [c7]Andrew D. Ker, Tomás Pevný, Jan Kodovský, Jessica J. Fridrich:
The square root law of steganographic capacity. MM&Sec 2008: 107-116 - [c6]Tomás Pevný, Jessica J. Fridrich:
Novelty detection in blind steganalysis. MM&Sec 2008: 167-176 - [c5]Tomás Pevný, Jessica J. Fridrich:
Estimation of primary quantization matrix for steganalysis of double-compressed JPEG images. Security, Forensics, Steganography, and Watermarking of Multimedia Contents 2008: 681911 - 2007
- [c4]Jessica J. Fridrich, Tomás Pevný, Jan Kodovský:
Statistically undetectable jpeg steganography: dead ends challenges, and opportunities. MM&Sec 2007: 3-14 - [c3]Tomás Pevný, Jessica J. Fridrich:
Merging Markov and DCT features for multi-class JPEG steganalysis. Security, Steganography, and Watermarking of Multimedia Contents 2007: 650503 - 2006
- [c2]Tomás Pevný, Jessica J. Fridrich:
Multi-class blind steganalysis for JPEG images. Security, Steganography, and Watermarking of Multimedia Contents 2006: 60720O - 2005
- [c1]Tomás Pevný, Jessica J. Fridrich:
Towards Multi-class Blind Steganalyzer for JPEG Images. IWDW 2005: 39-53
Editorship
- 2021
- [e3]Dirk Borghys, Patrick Bas, Luisa Verdoliva, Tomás Pevný, Bin Li, Jennifer Newman:
IH&MMSec '21: ACM Workshop on Information Hiding and Multimedia Security, Virtual Event, Belgium, June, 22-25, 2021. ACM 2021, ISBN 978-1-4503-8295-3 [contents] - 2020
- [e2]Christian Riess, Franziska Schirrmacher, Irene Amerini, Paolo Bestagini, Tomás Pevný:
IH&MMSec '20: ACM Workshop on Information Hiding and Multimedia Security, Denver, CO, USA, June 22-24, 2020. ACM 2020, ISBN 978-1-4503-7050-9 [contents] - 2011
- [e1]Tomás Filler, Tomás Pevný, Scott Craver, Andrew D. Ker:
Information Hiding - 13th International Conference, IH 2011, Prague, Czech Republic, May 18-20, 2011, Revised Selected Papers. Lecture Notes in Computer Science 6958, Springer 2011, ISBN 978-3-642-24177-2 [contents]
Informal and Other Publications
- 2026
- [i44]Jiri Nemecek, Mark Kozdoba, Illia Kryvoviaz, Tomás Pevný, Jakub Marecek:
Intersectional Fairness via Mixed-Integer Optimization. CoRR abs/2601.19595 (2026) - [i43]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Tackle CSM in JPEG Steganalysis with Data Adaptation. CoRR abs/2605.21523 (2026) - 2025
- [i42]Jiri Nemecek, Mark Kozdoba, Illia Kryvoviaz, Tomás Pevný, Jakub Marecek:
Bias Detection via Maximum Subgroup Discrepancy. CoRR abs/2502.02221 (2025) - [i41]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs. CoRR abs/2503.12162 (2025) - [i40]Martin Rektoris, Milan Papez, Václav Smídl, Tomás Pevný:
Sparse Probabilistic Graph Circuits. CoRR abs/2508.07763 (2025) - [i39]Armin Hadzic, Milan Papez, Tomás Pevný:
Distillation of a tractable model from the VQ-VAE. CoRR abs/2509.01400 (2025) - [i38]Etienne Levecque, Aurélien Noirault, Tomás Pevný, Jan Butora, Patrick Bas, Rémi Cogranne:
Targeted Pooled Latent-Space Steganalysis Applied to Generative Steganography, with a Fix. CoRR abs/2510.12414 (2025) - 2024
- [i37]Jiri Nemecek, Tomás Pevný, Jakub Marecek:
Generating Likely Counterfactuals Using Sum-Product Networks. CoRR abs/2401.14086 (2024) - [i36]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Blind Data Adaptation to tackle Covariate Shift in Operational Steganalysis. CoRR abs/2405.16961 (2024) - [i35]Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer:
Malicious Internet Entity Detection Using Local Graph Inference. CoRR abs/2408.03287 (2024) - [i34]Milan Papez, Martin Rektoris, Tomás Pevný, Václav Smídl:
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs. CoRR abs/2408.07394 (2024) - [i33]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
GraphSPNs: Sum-Product Networks Benefit From Canonical Orderings. CoRR abs/2408.09451 (2024) - 2023
- [i32]Vít Skvára, Tomás Pevný, Václav Smídl:
Is AUC the best measure for practical comparison of anomaly detectors? CoRR abs/2305.04754 (2023) - [i31]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios. CoRR abs/2305.17246 (2023) - [i30]Jiri Nemecek, Tomás Pevný, Jakub Marecek:
Improving the Validity of Decision Trees as Explanations. CoRR abs/2306.06777 (2023) - [i29]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Leveraging Data Geometry to Mitigate CSM in Steganalysis. CoRR abs/2310.04479 (2023) - [i28]Leah Chrestien, Tomás Pevný, Stefan Edelkamp, Antonín Komenda:
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal. CoRR abs/2310.19463 (2023) - 2022
- [i27]Tomás Pevný, Viliam Lisý, Branislav Bosanský, Petr Somol, Michal Pechoucek:
Explaining Classifiers Trained on Raw Hierarchical Multiple-Instance Data. CoRR abs/2208.02694 (2022) - [i26]Leah Chrestien, Tomás Pevný, Antonín Komenda, Stefan Edelkamp:
A Differentiable Loss Function for Learning Heuristics in A. CoRR abs/2209.05206 (2022) - [i25]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Using Set Covering to Generate Databases for Holistic Steganalysis. CoRR abs/2211.03447 (2022) - 2021
- [i24]Simon Mandlík, Tomás Pevný:
Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks. CoRR abs/2104.09650 (2021) - [i23]Simon Mandlík, Matej Racinsky, Viliam Lisý, Tomás Pevný:
Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data. CoRR abs/2105.09107 (2021) - [i22]Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomás Pevný:
When Should You Defend Your Classifier - A Game-theoretical Analysis of Countermeasures against Adversarial Examples. CoRR abs/2108.07602 (2021) - [i21]Milan Papez, Tomás Pevný, Václav Smídl:
Fitting large mixture models using stochastic component selection. CoRR abs/2110.04776 (2021) - [i20]Leah Chrestien, Tomás Pevný, Antonín Komenda, Stefan Edelkamp:
Heuristic Search Planning with Deep Neural Networks using Imitation, Attention and Curriculum Learning. CoRR abs/2112.01918 (2021) - 2020
- [i19]Tomás Pevný, Marek Dedic:
Nested Multiple Instance Learning in Modelling of HTTP network traffic. CoRR abs/2002.04059 (2020) - [i18]Lukás Adam, Václav Mácha, Václav Smídl, Tomás Pevný:
General Framework for Binary Classification on Top Samples. CoRR abs/2002.10923 (2020) - [i17]Tomás Pevný, Václav Smídl, Martin Trapp, Ondrej Polácek, Tomás Oberhuber:
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations. CoRR abs/2005.01297 (2020) - [i16]Niklas Heim, Tomás Pevný, Václav Smídl:
Neural Power Units. CoRR abs/2006.01681 (2020) - [i15]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks. CoRR abs/2009.12462 (2020) - [i14]Vít Skvára, Jan Francu, Matej Zorek, Tomás Pevný, Václav Smídl:
Comparison of Anomaly Detectors: Context Matters. CoRR abs/2012.06260 (2020) - 2019
- [i13]Václav Smídl, Jan Bím, Tomás Pevný:
Anomaly scores for generative models. CoRR abs/1905.11890 (2019) - [i12]Tomás Pevný, Vojtech Kovarík:
Approximation capability of neural networks on spaces of probability measures and tree-structured domains. CoRR abs/1906.00764 (2019) - [i11]Paul Prasse, René Knaebel, Lukás Machlica, Tomás Pevný, Tobias Scheffer:
Joint Detection of Malicious Domains and Infected Clients. CoRR abs/1906.09084 (2019) - [i10]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features as a Sequential Decision-Making Problem. CoRR abs/1909.02564 (2019) - [i9]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces. CoRR abs/1911.08756 (2019) - [i8]Niklas Heim, Václav Smídl, Tomás Pevný:
Rodent: Relevance determination in ODE. CoRR abs/1912.00656 (2019) - 2018
- [i7]Vyacheslav Kungurtsev, Tomás Pevný:
Algorithms for solving optimization problems arising from deep neural net models: smooth problems. CoRR abs/1807.00172 (2018) - [i6]Vyacheslav Kungurtsev, Tomás Pevný:
Algorithms for solving optimization problems arising from deep neural net models: nonsmooth problems. CoRR abs/1807.00173 (2018) - [i5]Vít Skvára, Tomás Pevný, Václav Smídl:
Are generative deep models for novelty detection truly better? CoRR abs/1807.05027 (2018) - 2017
- [i4]Tomás Pevný, Petr Somol:
Discriminative models for multi-instance problems with tree-structure. CoRR abs/1703.02868 (2017) - [i3]Jan Stiborek, Tomás Pevný, Martin Rehák:
Multiple Instance Learning for Malware Classification. CoRR abs/1705.02268 (2017) - [i2]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features using Deep Reinforcement Learning. CoRR abs/1711.07364 (2017) - 2016
- [i1]Tomás Pevný, Petr Somol:
Using Neural Network Formalism to Solve Multiple-Instance Problems. CoRR abs/1609.07257 (2016)
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-08-18 00:07 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated, funded, and maintained by:
Schloss Dagstuhl - Leibniz Center for Informatics is a member of the Leibniz Association and is funded by the federal government of Germany and the states of Germany, especially Saarland and Rhineland‑Palatinate.
