Ing. Jiří Vomlel, Ph.D.
senior research fellow

Department:
Department of Decision-Making Theory
Research interests:
Probabilistic methods in Artificial Intelligence, Bayesian networks
Biography
Publication list
Education
- 1992 - 2000, Ph.D. in Artificial Intelligence, Faculty of Electrical Engineering of the Czech Technical University in Prague
- 1987 - 1992, MSc. in Technical Cybernetics, Faculty of Electrical Engineering of the Czech Technical University in Prague
- 1983 - 1987, Gymnazium in Jihlava
Work Experience
- 2006 - now, Faculty of Management, University of Economics, Jindřichův Hradec
- 1994 - 1999, 2002 - now, Department of Decision-making Theory, Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague
- 1997 - 2000, 2002 - 2004, Laboratory for Intelligent Systems (LISp), University of Economics, Prague
- 1999 - 2002, The Research Unit of Decision Support Systems, Aalborg University, Denmark
- 1992 - 1994, Transcom Ltd. Prague
Research Interests
- Uncertainty in Artificial Intelligence
- Probabilistic Methods in Artificial Intelligence
- Probabilistic Graphical Models
- Bayesian Networks
- Computerized Adaptive Testing (CAT)
- Decision Theoretic Troubleshooting
- Marginal Problem
Research Projects
- Project GA20-18407S - Verb Class Analysis Accelerator for Low-Resource Languages - RoboCorp (2020–2022)
- Project GA19-04579S - Conditional independence structures: methods of polyhedral geometry (2019–2021)
- Project GA14-13713S - Tensor Decomposition Methods and Their Applications (2014–2016)
- Project GA13-20012S - Conditional independence structures: algebraic and geometric approaches (2013–2015)
- Project GA201/09/1891 - Multidimensional Models of Uncertainty (2009–2011)
- Project GA201/08/0539 - Conditional independence structures: graphical and algebraic approaches (2008–2012)
- Project GEICC/08/E010 - The logic of causal and probabilistic reasoning in uncertain environments (2008–2011)
- Project 2C06019 - (Medical) Knowledge Acquisition and Modelling (2006–2011)
- Project 1M0572 - Data, algorithms, decision making (2005–2011)
Conferences we organize/have organized
- WUPES'22 – 12th Workshop on Uncertainty Processing, Kutná Hora, Czechia
- ECSQARU'21 – 16th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Prague, Czechia
- WUPES'18 – 11th Workshop on Uncertainty Processing, Třeboň, Czechia
- PGM'18 – 9th International Conference on Probabilistic Graphical Models, Prague, Czechia
- WUPES'15 – 10th Workshop on Uncertainty Processing, Monínec, Czechia
- WUPES'12 – 9th Workshop on Uncertainty Processing, Marianské Lázně, Czechia
- WUPES'09 – 8th Workshop on Uncertainty Processing, Liblice, Czechia
- PGM'06 – 3rd European Workshop on Probabilistic Graphical Models, Prague, Czechia
- WUPES'06 – 7th Workshop on Uncertainty Processing, Mikulov, Czechia
- WUPES'03 – 6th Workshop on Uncertainty Processing, Hejnice, Czechia
Current PhD students
- Martin Rod – Models of corporate architecture in the environment of public administration and their effective management and transformation based on uncertainty models
- Iván Leonardo Pérez Cabrera – Probabilistic Graphical Models for Computerized Adaptive Testing
PhD graduates
- Issam Salman – Machine learning methods for analyzing medical data
- Martin Plajner – Adaptive Testing using Bayesian Networks
- Jan Švorc – Subjective Well-Being and Individual Material Situation in Four Countries of Central Europe
- Václav Lín – On sequencing problems in the management of troubleshooting operations
Current MSc students
- Barbora Bumbálková – Explainable artificial intelligence models for knowledge testing
- Jan Makyda – Analysis of conspiracy and disinformation narratives using Bayesian networks
- Lucie Čondlová – Bayesian networks for e-learning and assessment systems in education
MSc graduates
- František Komanec – Webový systém pro testovaní znalostí studentů
- Kristína Blašková – Machine learning methods for sleep analysis
- Amal Magauina – Application of Bayesian Networks in Adaptive Knowledge Testing of Students
- Václav Lín – Optimal Observation Strategies for Bayesian Networks
Professional activities
- Area Editor of the International Journal of Approximate Reasoning
- Program committee member of the UAI Conference since 2003
- Program committee member of the IJCAI Conference since 2018
- Program committee member of the PGM Conference since 2010
- Program committee member of the ECSQARU Conference since 2013
- Program committee member of AISTATS since 2020
- Member of the Institute Board of the Institute of Information Theory and Automation, Czech Academy of Sciences since 2022
Books and chapters
- Improved Industrial Risk Analysis via a Human Factor-Driven Bayesian Network Approach, Analytics Modeling in Reliability and Machine Learning and Its Applications, p. 1-349 Download Download DOI: 10.1007/978-3-031-72636-1_2 [2025] :
- Graphical and Algebraic Representatives of Conditional Independence Models, Advances in Probabilistic Graphical Models, p. 55-80, Eds: Lucas Peter, Gámez José A., Salmerón Antonio [2007] :
Journal articles
- Structural learning of mixed noisy-OR Bayesian networks, International Journal of Approximate Reasoning 161 Download Download DOI: 10.1016/j.ijar.2023.108990 [2023] :
- Learning the Structure of Bayesian Networks from Incomplete Data Using a Mixture Model, International Journal of Computing and Informatics 47 1 (2023), p. 83-96 Download Download DOI: 10.31449/inf.v47i1.4497 [2023] :
- Aspectual pairing and aspectual classes in Abui, STUF-Language Typology and Universals 74, p. 621-657 Download Download DOI: 10.1515/stuf-2021-1046 [2021] :
- Learning bipartite Bayesian networks under monotonicity restrictions, International Journal of General Systems 49 1 (2020), p. 88-111 Download Download DOI: 10.1080/03081079.2019.1692004 [2020] :
- The magnetic nature of umbra-penumbra boundary in sunspots, Astronomy & Astrophysics 611 DOI: 10.1051/0004-6361/201732528 [2018] :
- An empirical comparison of popular structure learning algorithms with a view to gene network inference, International Journal of Approximate Reasoning 88 1 (2017), p. 602-613 Download DOI: 10.1016/j.ijar.2016.12.012 [2017] :
- Influence diagrams for speed profile optimization, International Journal of Approximate Reasoning 88 1 (2017), p. 567-586 Download DOI: 10.1016/j.ijar.2016.11.018 [2017] :
- Generalizations of the noisy-or model, Kybernetika 51 3 (2015), p. 508-524 Download DOI: 10.14736/kyb-2015-3-0508 [2015] :
- Probabilistic inference with noisy-threshold models based on a CP tensor decomposition, International Journal of Approximate Reasoning 55 4 (2014), p. 1072-1092 Download DOI: 10.1016/j.ijar.2013.12.002 [2014] :
- All roads lead to Rome - New search methods for the optimal triangulation problem, International Journal of Approximate Reasoning 53 9 (2012), p. 1350-1366 Download DOI: 10.1016/j.ijar.2012.06.006 [2012] :
- Rank of tensors of l-out-of-k functions: an application in probabilistic inference, Kybernetika 47 3 (2011), p. 317-336 Download [2011] :
- On open questions in the geometric approach to structural learning Bayesian nets, International Journal of Approximate Reasoning 52 5 (2011), p. 627-640 Download DOI: 10.1016/j.ijar.2010.09.004 [2011] :
- A geometric view on learning Bayesian network structures, International Journal of Approximate Reasoning 51 5 (2010), p. 578-586 Download DOI: 10.1016/j.ijar.2010.01.014 [2010] :
- A reconstruction algorithm for the essential graph, International Journal of Approximate Reasoning 50 2 (2009), p. 385-413 Download DOI: 10.1016/j.ijar.2008.09.001 [2009] :
- Assessing the performance of variational methods for mixed logistic regression models, Journal of Statistical Computation and Simulation 78 8 (2008), p. 765-779 DOI: 10.1080/00949650701282507 [2008] :
- Exploiting Tensor Rank-One Decomposition in Probabilistic Inference, Kybernetika 43 5 (2007), p. 747-764 Download [2007] :
- Noisy-or classifier, International Journal of Intelligent Systems 21 3 (2006), p. 381-389 [2006] :
- Probabilistic reasoning with uncertain evidence, Neural Network World 15 5 (2004), p. 453-465 [2004] :
- Integrating inconsistent data in a probabilistic model, Journal of Applied Non-Classical Logics 14 3 (2004), p. 367-386 [2004] :
- Building adaptive tests using Bayesian networks, Kybernetika 40 3 (2004), p. 333-348 [2004] :
- A prototypical system for soft evidential update, Applied Intelligence 21 1 (2004), p. 81-97 [2004] :
- Bayesian networks in educational testing, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 12 1 (2004), p. 83-100 [2004] :
Other publications
- Enhancing Bayesian Networks with Psychometric Models, Proceedings of Machine Learning Research (PMLR), Volume 246 : International Conference on Probabilistic Graphical Models, p. 401-414 Download Download [2024] :
- Uncovering Relationships using Bayesian Networks: A Case Study on Conspiracy Theories, Proceedings of Machine Learning Research (PMLR), Volume 246 : International Conference on Probabilistic Graphical Models, p. 470-485 Download Download [2024] :
- On Identifiability of BN2A Networks, Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2023., p. 136-148, Eds: Bouraoui Zied, Vesic Srdjan Download DOI: 10.1007/978-3-031-45608-4_11 [2023] :
- Improving Czech Digital Government Based on Quantified Maturity Model of Enterprise Architecture, Proceedings of the 25th International Conference on Enterprise Information Systems, p. 600-607, Eds: Filipe Joaquim, Śmiałek Michał, Brodsky Alexander, Hammoudi Slimane Download DOI: 10.5220/0011855300003467 [2023] :
- Automatic Verb Classifier for Abui (AVC-abz), Proceedings of the Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference, p. 42-50 Download [2022] :
- On the rank of 2×2×2 probability tables, Proceedings of Machine Learning Research, Volume 186 : Proceedings of The 11th International Conference on Probabilistic Graphical Models, p. 361-372, Eds: Salmerón Antonio, Rumí Rafael Download [2022] :
- Learning Noisy-Or Networks with an Application in Linguistics, Proceedings of Machine Learning Research, Volume 186 : Proceedings of The 11th International Conference on Probabilistic Graphical Models, p. 277-288, Eds: Salmerón Antonio, Rumí Rafael Download [2022] :
- Modeling the spread of loanwords in South-East Asia using sailing navigation software and Bayesian networks, Proceedings of the 12th Workshop on Uncertainty Processing, p. 135-146, Eds: Studený Milan, Ay Nihat, Coletti Giulianella, Kleiter Gernot D., Shenoy Prakash P. Download [2022] :
- Bayesian Networks for the Test Score Prediction: A Case Study on a Math Graduation Exam, Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2021., p. 255-267, Eds: Vejnarová Jiřina, Wilson Nic Download DOI: 10.1007/978-3-030-86772-0_19 [2021] :
- Integrating the human factor in FMECA-based risk evaluation through Bayesian networks, Modelling for Engineering & Human Behaviour 2020, p. 24-29 Download [2020] :
- Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach, ÚTIA AV ČR (Praha, 2020) Download [2020] :
- Bayesian Networks for the Analysis of Subjective Well-Being, Proceedings of the 22nd Czech-Japan Seminar on Data Analysis and Decision Making (CJS’19), p. 175-188, Eds: Inuiguchi Masahiro, Jiroušek Radim, Kratochvíl Václav Download [2019] :
- On irreducible min-balanced set systems, Symbolic and Quantitative Approaches to Reasoning with Uncertainty : 15th European Conference, ECSQARU 2019, Belgrade, Serbia, September 18-20, 2019, p. 444-454, Eds: Kern-Isberner G., Ognjanovic Z. Download DOI: 10.1007/978-3-030-29765-7_37 [2019] :
- Representations of Bayesian Networks by Low-Rank Models, Proceedings of Machine Learning Research, p. 463-472, Eds: Kratochvíl Václav, Studený Milan Download [2018] :
- Gradient Descent Parameter Learning of Bayesian Networks under Monotonicity Restrictions, Proceedings of the 11th Workshop on Uncertainty Processing (WUPES’18), p. 153-164, Eds: Kratochvíl Václav, Vejnarová Jiřina Download [2018] :
- Employing Bayesian Networks for Subjective Well-being Prediction, Proceedings of the 11th Workshop on Uncertainty Processing (WUPES’18), p. 189-204, Eds: Kratochvíl Václav, Vejnarová Jiřina Download [2018] :
- Dynamic Bayesian Networks for the Classification of Sleep Stages, Proceedings of the 11th Workshop on Uncertainty Processing (WUPES’18), p. 205-215, Eds: Kratochvíl Václav, Vejnarová Jiřina Download [2018] :
- Question Selection Methods for Adaptive Testing with Bayesian Networks, Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 164-175, Eds: Novák V., Inuiguchi M., Štěpnička M. Download [2017] :
- A machine learning method for incomplete and imbalanced medical data, Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, CZECH-JAPAN SEMINAR 2017, p. 188-195, Eds: Novák Vilém, Inuiguchi Masahiro, Štěpnička Martin Download [2017] :
- Solving Trajectory Optimization Problems by Influence Diagrams, Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2017, p. 146-155, Eds: Antonucci A., Cholvy L., Papini O. Download DOI: 10.1007/978-3-319-61581-3_14 [2017] :
- Monotonicity in Bayesian Networks for Computerized Adaptive Testing, Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2017, p. 125-134, Eds: Antonucci A., Cholvy L., Papini O. Download DOI: 10.1007/978-3-319-61581-3_12 [2017] :
- Student Skill Models in Adaptive Testing, Proceedings of the Eighth International Conference on Probabilistic Graphical Models, p. 403-414, Eds: Antonucci A., Corani G., Polpo de Campos C. Download [2016] :
- Influence Diagrams for the Optimization of a Vehicle Speed Profile, Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), p. 44-53, Eds: Agosta J. M., Carvalho R. N. Download [2016] :
- Bayesian Network Models for Adaptive Testing, Proceedings of the Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015) co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), p. 24-33, Eds: Agosta J. M., Carvalho R. N. Download [2016] :
- An empirical comparison of popular algorithms for learning gene networks, Proceedings of the 10th Workshop on Uncertainty Processing WUPES’15, p. 61-72 Download [2015] :
- Influence diagrams for speed profile optimization" computational issues, Proceedings of the 10th Workshop on Uncertainty Processing WUPES’15, p. 203-216 Download [2015] :
- An Approximate Tensor-Based Inference Method Applied to the Game of Minesweeper, Probabilistic Graphical Models, p. 535-550, Eds: van der Gaag Linda C. , Feelders Ad J. Download DOI: 10.1007/978-3-319-11433-0_35 [2014] :
- Probabilistic Inference in BN2T Models by Weighted Model Counting, Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence, p. 275-284, Eds: Jaeger Manfred, Nielsen Thomas Dyhre, Viappiani Paolo Download DOI: 10.3233/978-1-61499-330-8-275 [2013] :
- A generalization of the noisy-or model to multivalued parent variables, Proceedings of the 16th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty (CJS-2013), p. 19-27 Download [2013] :
- Machine Learning Methods for Mortality Prediction in Patients with ST Elevation Myocardial Infarction, Proceedings of The Ninth Workshop on Uncertainty Processing, p. 204-213, Eds: Kroupa Tomáš, Vejnarová Jiřina Download [2012] :
- Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition, Proceedings of The Sixth European Workshop on Probabilistic Graphical Models, p. 355-362 Download [2012] :
- Predikce hospitalizační mortality u akutního infarktu myokardu, Sborník příspěvků MEDSODFT 2011, p. 128-138 Download [2011] :
- All roads lead to Rome — New search methods for optimal triangulations, Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010), p. 209-216 Download [2010] :
- Honour Thy Neighbour — Clique Maintenance in Dynamic Graphs, Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010), p. 201-208 Download [2010] :
- Polyhedral approach to statistical learning graphical models, Abstracts of The 2nd CREST-SBM International Conference on Harmony of Groebner Bases and the Moderm Industrial Socienty, p. 1-4 Download [2010] :
- Applying Bayesian networks in the game of Minesweeper, Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 153-162, Eds: Novák V., Pavliska V., Štěpnička M. Download [2009] :
- An experimental comparison of triangulation heuristics on transformed BN2O networks, Proceedings of the 8th Workshop on Uncertainty Processing, p. 251-260, Eds: Kroupa Tomáš, Vejnarová Jiřina Download [2009] :
- On open questions in the geometric approach to learning BN structures, WUPES'09, p. 226-236, Eds: Kroupa T., Vejnarová J. Download [2009] :
- Triangulation Heuristics for BN2O Networks, Symbolic and Quantitative Approaches to Reasoning with Uncertainty, p. 566-577, Eds: Sossai C., Chemello G. DOI: 10.1007/978-3-642-02906-6_49 [2009] :
- A Geometric Approach to Learning BN Structures, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), p. 281-288, Eds: Jaeger Manfred, Nielsen Thomas D. Download [2008] :
- Arithmetic circuits of the noisy-or models, Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM'08), p. 297-304, Eds: Jaeger Manfred , Nielsen Thomas D. Download [2008] :
- An evaluation of string similarity measures on pricelists of computer components, Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./, p. 1-6, Eds: Kroupa T., Vejnarová J. [2007] :
- Using imsets for learning Bayesian networks, Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./, p. 178-189, Eds: Kroupa T., Vejnarová J. [2007] :
- Exploiting Tensor Rank-one Decomposition in Probabilistic Inference, ÚTIA AV ČR (Praha, 2006) [2006] :
- Proceedings of the 3th European Workshop on Probabilistic Graphical Models, Agentura Action M (Praha, 2006) [2006]
- Tensor Rank-One Decomposition of Probability Tables, IPMU 2006. Information Processing and Management of Uncertainty in Knowledge-Based Systems, p. 2292-2299, Eds: Bouchon-Meunier B., Yager R. R. [2006] :
- Decomposition of probability tables representing Boolean functions, Proceedings of the 8th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 159-166, Eds: Kroupa T., Vejnarová J., Oeconomica (Praha, 2005) [2005] :
- Decision support system for comparison of price lists, Proceedings of the 8th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 32-38, Eds: Kroupa T., Vejnarová J., Oeconomica (Praha, 2005) [2005] :
- Tensor Rank-One Decomposition of Probability Tables, ÚTIA AV ČR (Praha, 2005) [2005] :
- Transition between graphical and algebraic representatives of Bayesian network models, Proceedings of the Second European Workshop on Probabilistic Graphical Models, p. 193-200 [2004] :
- Bayesian networks in Mastermind, Proceedings of the 7th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty, p. 185-190 [2004] :
- Thoughts on belief and model revision with uncertain evidence, Znalosti 2004. Sborník příspěvků 3.ročníku konference, p. 126-137 [2004] :
- Noisy-or classifier, Proceedings of the 6th Workshop on Uncertainty Processing, p. 291-302, University of Economics (Prague, 2003) [2003] :
- Integrating inconsistent data in a probabilistic model, Uncertainty, Incompleteness, Imprecision and Conflict in Multiple Data Sources, p. 1-10, Eds: Liu W., Cholvy L., Benferhat S., UUJ (Aalborg, 2003) [2003] :
- Two applications of Bayesian networks, Znalosti 2003. Sborník příspěvků 2. ročníku konference, p. 73-82, VŠB (Ostrava, 2003) [2003] :
- Bayesian networks in educational testing, Proceedings of the First European Workshop on Probabilistic Graphical Models, p. 176-185, Eds: Gámez J. A., Salmerón A., University of Castilla (Cuenca, 2002) [2002] :
- Methods of Probabilistic Knowledge Integration. Ph.D. Thesis (1999) [1999] :
- Statistical methods for probabilistic model parameter estimation from incomplete data and their application to the marginal problem, Proceedings of the 4th Workshop on Uncertainty Processing, p. 184-193, VŠE (Praha, 1997) [1997] :
- Inconsistent knowledge integration in a probabilistic model, Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, p. 263-270, Eds: Colleti G., Dubois D., Scozzafava R., Plenum Press (New York, 1995) [1995] :