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Arjen Hommersom
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- affiliation: Open University of the Netherlands
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2020 – today
- 2024
- [j20]Raphaela Butz
, Arjen Hommersom
Evaluating the Usefulness of Counterfactual Explanations from Bayesian Networks. Hum. Centric Intell. Syst. 4(2): 286-298 (2024) - 2023
- [c39]Wesley de Kraker, Harald Vranken
GLICE: Combining Graph Neural Networks and Program Slicing to Improve Software Vulnerability Detection. EuroS&P Workshops 2023: 34-41 - 2022
- [j19]Raphaela Butz
Investigating the understandability of XAI methods for enhanced user experience: When Bayesian network users became detectives. Artif. Intell. Medicine 134: 102438 (2022) - 2021
- [j18]Giso H. Dal
A compositional approach to probabilistic knowledge compilation. Int. J. Approx. Reason. 138: 38-66 (2021) - [i3]Raphaela Butz, Renée Schulz, Arjen Hommersom, Marko C. J. D. van Eekelen:
What is understandable in Bayesian network explanations? CoRR abs/2110.01322 (2021) - 2020
- [c38]Simone C. M. W. Tummers, Arjen Hommersom
Gaining Insight into Determinants of Physical Activity Using Bayesian Network Learning. BNAIC/BENELEARN (Selected Papers) 2020: 172-187 - [c37]Marcos L. P. Bueno, Arjen Hommersom
Temporal Exceptional Model Mining Using Dynamic Bayesian Networks. AALTD@PKDD/ECML 2020: 97-112
2010 – 2019
- 2019
- [j17]Manxia Liu, Fabio Stella, Arjen Hommersom
A comparison between discrete and continuous time Bayesian networks in learning from clinical time series data with irregularity. Artif. Intell. Medicine 95: 104-117 (2019) - [j16]Marcos L. P. Bueno, Arjen Hommersom
A probabilistic framework for predicting disease dynamics: A case study of psychotic depression. J. Biomed. Informatics 95 (2019) - [c36]Marcos L. P. Bueno, Arjen Hommersom
A Data-Driven Exploration of Hypotheses on Disease Dynamics. AIME 2019: 170-179 - 2018
- [j15]Arjen Hommersom
Probabilistic logic programming (PLP) 2016. Int. J. Approx. Reason. 96: 56 (2018) - [c35]Jorrit Kronjee, Arjen Hommersom
Discovering software vulnerabilities using data-flow analysis and machine learning. ARES 2018: 6:1-6:10 - [c34]Eef van Es, Harald P. E. Vranken, Arjen Hommersom
Denial-of-Service Attacks on LoRaWAN. ARES 2018: 17:1-17:6 - [c33]Manxia Liu, Fabio Stella, Arjen Hommersom
Representing Hypoexponential Distributions in Continuous Time Bayesian Networks. IPMU (3) 2018: 565-577 - [c32]Manxia Liu, Fabio Stella, Arjen Hommersom, Peter J. F. Lucas:
Making Continuous Time Bayesian Networks More Flexible. PGM 2018: 237-248 - [c31]Raphaela Butz, Arjen Hommersom
Explaining the Most Probable Explanation. SUM 2018: 50-63 - [c30]Marcos L. P. Bueno, Arjen Hommersom
Modeling the Dynamics of Multiple Disease Occurrence by Latent States. SUM 2018: 93-107 - 2017
- [j14]Manxia Liu, Arjen Hommersom
Hybrid time Bayesian networks. Int. J. Approx. Reason. 80: 460-474 (2017) - [j13]Marcos L. P. Bueno
Asymmetric hidden Markov models. Int. J. Approx. Reason. 88: 169-191 (2017) - [j12]Hossein Amirkhani, Mohammad Rahmati, Peter J. F. Lucas, Arjen Hommersom
Exploiting Experts' Knowledge for Structure Learning of Bayesian Networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2154-2170 (2017) - [c29]Simon Rabinowicz
A Prognostic Model of Glioblastoma Multiforme Using Survival Bayesian Networks. AIME 2017: 81-85 - [c28]Marcos Luiz de Paula Bueno, Arjen Hommersom, Peter J. F. Lucas:
An improved diagnostic method for probabilistic consistency-based diagnosis. DX 2017: 65-77 - 2016
- [j11]Marcos L. P. Bueno
Understanding disease processes by partitioned dynamic Bayesian networks. J. Biomed. Informatics 61: 283-297 (2016) - [c27]Steffen Michels, Arjen Hommersom, Peter J. F. Lucas:
Approximate Probabilistic Inference with Bounded Error for Hybrid Probabilistic Logic Programming. IJCAI 2016: 3616-3622 - [c26]Arjen Hommersom, Marcos L. P. Bueno:
Toward Computing Conflict-Based Diagnoses in Probabilistic Logic Programming. PLP@ILP 2016: 29-38 - [c25]Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Sicco Verwer, Alexis Linard:
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case. Probabilistic Graphical Models 2016: 50-61 - [c24]Manxia Liu, Arjen Hommersom, Maarten van der Heijden, Peter J. F. Lucas:
Learning Parameters of Hybrid Time Bayesian Networks. Probabilistic Graphical Models 2016: 287-298 - [e2]Arjen Hommersom, Samer A. Abdallah:
Proceedings of the 3rd International Workshop on Probabilistic Logic Programming co-located with 26th International Conference on Inductive Logic Programming (ILP 2016), London, UK, September 3, 2016. CEUR Workshop Proceedings 1661, CEUR-WS.org 2016 [contents] - [i2]Jessa Bekker, Arjen Hommersom, Martijn Lappenschaar, Jesse Davis:
Measuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks. CoRR abs/1612.03055 (2016) - 2015
- [j10]Steffen Michels, Arjen Hommersom
A new probabilistic constraint logic programming language based on a generalised distribution semantics. Artif. Intell. 228: 1-44 (2015) - [j9]Peter J. F. Lucas, Arjen Hommersom
Modeling the Interactions between Discrete and Continuous Causal Factors in Bayesian Networks. Int. J. Intell. Syst. 30(3): 209-235 (2015) - [c23]Tim Op De Beéck, Arjen Hommersom
Mining Hierarchical Pathology Data Using Inductive Logic Programming. AIME 2015: 76-85 - [c22]Manxia Liu, Arjen Hommersom
Hybrid Time Bayesian Networks. ECSQARU 2015: 376-386 - [p8]Peter J. F. Lucas, Arjen Hommersom
How to Read the Book "Foundations of Biomedical Knowledge Representation". Foundations of Biomedical Knowledge Representation 2015: 3-7 - [p7]Arjen Hommersom
An Introduction to Knowledge Representation and Reasoning in Healthcare. Foundations of Biomedical Knowledge Representation 2015: 9-32 - [p6]Luca Anselma
Supporting Physicians and Patients Through Recommendation: Guidelines and Beyond. Foundations of Biomedical Knowledge Representation 2015: 281-286 - [p5]Luca Anselma
A Hybrid Approach to the Verification of Computer Interpretable Guidelines. Foundations of Biomedical Knowledge Representation 2015: 287-315 - [e1]Arjen Hommersom
Foundations of Biomedical Knowledge Representation - Methods and Applications. Lecture Notes in Computer Science 9521, Springer 2015, ISBN 978-3-319-28006-6 [contents] - 2014
- [j8]Martijn Lappenschaar, Arjen Hommersom
Qualitative chain graphs and their application. Int. J. Approx. Reason. 55(4): 957-976 (2014) - [c21]Steffen Michels, Arjen Hommersom, Peter J. F. Lucas, Marina Velikova:
Imprecise Probabilistic Horn Clause Logic. ECAI 2014: 621-626 - [c20]Maarten van der Heijden, Arjen Hommersom:
Causal Independence Models for Continuous Time Bayesian Networks. Probabilistic Graphical Models 2014: 503-518 - 2013
- [j7]Arjen Hommersom, Peter J. F. Lucas:
Probabilistic problem solving in biomedicine. Artif. Intell. Medicine 57(3): 169-170 (2013) - [j6]Martijn Lappenschaar, Arjen Hommersom, Peter J. F. Lucas, Joep Lagro, Stefan Visscher:
Multilevel Bayesian networks for the analysis of hierarchical health care data. Artif. Intell. Medicine 57(3): 171-183 (2013) - [c19]Arjen Hommersom, Sicco Verwer, Peter J. F. Lucas:
Discovering Probabilistic Structures of Healthcare Processes. KR4HC/ProHealth 2013: 53-67 - [c18]Martijn Lappenschaar, Arjen Hommersom, Joep Lagro, Peter J. F. Lucas:
Understanding the Co-occurrence of Diseases Using Structure Learning. AIME 2013: 135-144 - [c17]Arjen Hommersom, Peter J. F. Lucas, Marina Velikova, Giso H. Dal, Joaquim Bastos
MoSHCA - my mobile and smart health care assistant. Healthcom 2013: 188-192 - [c16]Steffen Michels, Arjen Hommersom, Peter J. F. Lucas, Marina Velikova, Pieter W. M. Koopman:
Inference for a New Probabilistic Constraint Logic. IJCAI 2013: 2540-2546 - [c15]Steffen Michels, Marina Velikova, Arjen Hommersom, Peter J. F. Lucas:
A Decision Support Model for Uncertainty Reasoning in Safety and Security Tasks. SMC 2013: 663-668 - 2012
- [c14]Martijn Lappenschaar, Arjen Hommersom, Peter J. F. Lucas:
Probabilistic Causal Models of Multimorbidity Concepts. AMIA 2012 - 2011
- [c13]Arjen Hommersom, Peter J. F. Lucas:
Generalising the Interaction Rules in Probabilistic Logic. IJCAI 2011: 912-917 - [p4]Arjen Hommersom, Peter J. F. Lucas, René Waarsing, Pieter W. M. Koopman:
Applying Bayesian Networks for Intelligent Adaptable Printing Systems. Solutions on Embedded Systems 2011: 201-213 - 2010
- [c12]Arjen Hommersom:
Toward Probabilistic Analysis of Guidelines. KR4HC 2010: 139-152 - [c11]Arjen Hommersom, Peter J. F. Lucas:
Using Bayesian Networks in an Industrial Setting: Making Printing Systems Adaptive. ECAI 2010: 401-406
2000 – 2009
- 2009
- [j5]Perry Groot, Arjen Hommersom, Peter J. F. Lucas, Robbert-Jan Merk, Annette ten Teije
Using model checking for critiquing based on clinical guidelines. Artif. Intell. Medicine 46(1): 19-36 (2009) - [c10]Arjen Hommersom, Nivea de Carvalho Ferreira, Peter J. F. Lucas:
Integrating Logical Reasoning and Probabilistic Chain Graphs. ECML/PKDD (1) 2009: 548-563 - [c9]Arjen Hommersom, Peter J. F. Lucas, René Waarsing, Pieter W. M. Koopman:
Applying Bayesian networks for intelligent adaptable printing systems. WISES 2009: 127-133 - 2008
- [j4]Arjen Hommersom, Peter J. F. Lucas, Patrick van Bommel:
Checking the quality of clinical guidelines using automated reasoning tools. Theory Pract. Log. Program. 8(5-6): 611-641 (2008) - [p3]Arjen Hommersom, Perry Groot, Michael Balser, Peter J. F. Lucas:
Formal Methods for Verification of Clinical Practice Guidelines. Computer-based Medical Guidelines and Protocols 2008: 63-80 - [p2]Perry Groot, Arjen Hommersom, Peter J. F. Lucas:
Adaptation of Clinical Practice Guidelines. Computer-based Medical Guidelines and Protocols 2008: 121-139 - [p1]Arjen Hommersom, Perry Groot, Peter J. F. Lucas, Mar Marcos
A Constraint-based Approach to Medical Guidelines and Protocols. Computer-based Medical Guidelines and Protocols 2008: 213-222 - [i1]Arjen Hommersom, Peter J. F. Lucas, Patrick van Bommel:
Checking the Quality of Clinical Guidelines using Automated Reasoning Tools. CoRR abs/0806.0250 (2008) - 2007
- [j3]Arjen Hommersom, Perry Groot, Peter J. F. Lucas, Michael Balser, Jonathan Schmitt:
Combining task execution and background knowledge for the verification of medical guidelines. Knowl. Based Syst. 20(2): 113-119 (2007) - [j2]Arjen Hommersom, Perry Groot, Peter J. F. Lucas, Michael Balser, Jonathan Schmitt:
Verification of Medical Guidelines Using Background Knowledge in Task Networks. IEEE Trans. Knowl. Data Eng. 19(6): 832-846 (2007) - [c8]Perry Groot, Arjen Hommersom, Peter J. F. Lucas, Radu Serban, Annette ten Teije, Frank van Harmelen
The Role of Model Checking in Critiquing Based on Clinical Guidelines. AIME 2007: 411-420 - [c7]Arjen Hommersom, Peter J. F. Lucas:
Actions with Failures in Interval Temporal Logic. CLIMA 2007: 22-41 - 2006
- [c6]Arjen Hommersom, Perry Groot, Peter J. F. Lucas, Michael Balser, Jonathan Schmitt:
Verification of Medical Guidelines Using Task Execution with Background Knowledge. ECAI 2006: 835-836 - [c5]Arjen Hommersom, Perry Groot, Peter J. F. Lucas, Michael Balser, Jonathan Schmitt:
Combining Task Execution and Background Knowledge for the Verification of Medical Guidelines. SGAI Conf. 2006: 3-16 - 2005
- [c4]Arjen Hommersom, Peter J. F. Lucas, Patrick van Bommel, Theo P. van der Weide:
A History-Based Algebra for Quality-Checking Medical Guidelines. AIME 2005: 161-165 - [c3]Arjen Hommersom, Peter J. F. Lucas, Patrick van Bommel:
Argumentation Systems for History-Based Construction of Medical Guidelines. BNAIC 2005: 135-142 - 2004
- [j1]Arjen Hommersom, John-Jules Ch. Meyer, Erik P. de Vink:
Update Semantics of Security Protocols. Synth. 142(2): 229-267 (2004) - [c2]Arjen Hommersom, Peter J. F. Lucas, Michael Balser:
Meta-level Verification of the Quality of Medical Guidelines Using Interactive Theorem Proving. JELIA 2004: 654-666 - [c1]Arjen Hommersom, John-Jules Ch. Meyer, Erik P. de Vink:
Toward Reasoning about Security Protocols: A Semantic Approach. LCMAS 2004: 53-75
Coauthor Index
aka: Marcos Luiz de Paula Bueno
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last updated on 2024-12-10 20:51 CET by the dblp team
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