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Tomas Pevny

About Tomas Pevny

Tomas Pevny, With an exceptional h-index of 38 and a recent h-index of 28 (since 2020), a distinguished researcher at Ceské vysoké ucení technické v Praze, specializes in the field of unsupervised learning, steganography, steganalysis, network security.

His recent articles reflect a diverse array of research interests and contributions to the field:

On the Economics of Adversarial Machine Learning

Analyzing encrypted traffic behavior using contextual traffic data

Deep anomaly detection on set data: Survey and comparison

Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal

Malicious Internet Entity Detection Using Local Graph Inference

Generating Likely Counterfactuals Using Sum-Product Networks

The non-zero-sum game of steganography in heterogeneous environments

Sum-Product-Set Networks

Tomas Pevny Information

University

Position

Artificial Intelligence Center

Citations(all)

9329

Citations(since 2020)

4818

Cited By

6889

hIndex(all)

38

hIndex(since 2020)

28

i10Index(all)

82

i10Index(since 2020)

62

Email

University Profile Page

Google Scholar

Tomas Pevny Skills & Research Interests

unsupervised learning

steganography

steganalysis

network security

Top articles of Tomas Pevny

On the Economics of Adversarial Machine Learning

IEEE Transactions on Information Forensics and Security

2024/3/20

Tomas Pevny
Tomas Pevny

H-Index: 26

Analyzing encrypted traffic behavior using contextual traffic data

2024/3/19

Deep anomaly detection on set data: Survey and comparison

2024/3/2

Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal

Advances in Neural Information Processing Systems

2024/2/13

Tomas Pevny
Tomas Pevny

H-Index: 26

Malicious Internet Entity Detection Using Local Graph Inference

IEEE Transactions on Information Forensics and Security

2024/1/31

Generating Likely Counterfactuals Using Sum-Product Networks

arXiv preprint arXiv:2401.14086

2024/1/25

Jiri Nemecek
Jiri Nemecek

H-Index: 17

Tomas Pevny
Tomas Pevny

H-Index: 26

The non-zero-sum game of steganography in heterogeneous environments

IEEE Transactions on Information Forensics and Security

2023/7/17

Sum-Product-Set Networks

2023/7/13

Detection of malware and malicious applications

2023/7/11

Improving the Validitity of Decision Trees as Explanations

arXiv preprint arXiv:2306.06777

2023/6/11

Jiri Nemecek
Jiri Nemecek

H-Index: 17

Tomas Pevny
Tomas Pevny

H-Index: 26

Is AUC the best measure for practical comparison of anomaly detectors?

arXiv preprint arXiv:2305.04754

2023/5/8

Machine learning outputs with high confidence explanations

2023/4/6

Leveraging Data Geometry to Mitigate CSM in Steganalysis

2023/12/4

Nasimemu: Network attack simulator & emulator for training agents generalizing to novel scenarios

2023/9/25

Jaromír Janisch
Jaromír Janisch

H-Index: 2

Viliam Lisý
Viliam Lisý

H-Index: 18

Heuristic Search Optimisation Using Planning and Curriculum Learning Techniques

2023/9/5

Antonín Komenda
Antonín Komenda

H-Index: 12

Using set covering to generate databases for holistic steganalysis

2022/12/12

Semi-supervised deep networks for plasma state identification

Plasma Physics and Controlled Fusion

2022/10/26

Backpack: A backpropagable adversarial embedding scheme

IEEE Transactions on Information Forensics and Security

2022/9/14

John Klein
John Klein

H-Index: 7

A Differentiable Loss Function for Learning Heuristics in A

arXiv preprint arXiv:2209.05206

2022/9/12

Tomas Pevny
Tomas Pevny

H-Index: 26

General framework for binary classification on top samples

Optimization Methods and Software

2022/9/3

Václav Mácha
Václav Mácha

H-Index: 3

See List of Professors in Tomas Pevny University(Ceské vysoké ucení technické v Praze)