Projects per year
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Relational and object oriented Bayesian networks
Jaeger, M., Nielsen, T. D. & Bangsø, O.
19/05/2010 → …
Project: Research
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Modularization of complex tasks
Olesen, K. G., Bangsø, O., Nielsen, T. D. & Jaeger, M.
19/05/2010 → 31/12/2015
Project: Research
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Research output
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Learning Aggregation Functions
Pellegrini, G., Tibo, A., Frasconi, P., Passerini, A. & Jaeger, M., 2021, Proceedings of the Thirty International Joint Conference on Artificial Intelligence (IJCAI-21). International Joint Conferences on Artificial IntelligenceResearch output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
Open Access -
A Complete Characterization of Projectivity for Statistical Relational Models
Jaeger, M. & Schulte, O., 2020, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20). International Joint Conferences on Artificial Intelligence, p. 4283-4290Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
Open Access3 Citations (Scopus) -
Approximating Euclidean by Imprecise Markov Decision Processes
Jaeger, M., Bacci, G., Bacci, G., Larsen, K. G. & Jensen, P. G., 2020, International Symposium on Leveraging Applications of Formal Methods (ISoLA 2020). Margaria, T. & Steffen, B. (eds.). Springer, p. 275-289 15 p. (Lecture Notes in Computer Science, Vol. 12476).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
4 Citations (Scopus) -
Automatic Anomaly Detection for Sewage Network Sensors
Tibo, A., Nielsen, T. D., Jaeger, M., Ahm, M. & Rasch, P., 2020.Research output: Contribution to conference without publisher/journal › Conference abstract for conference › Research › peer-review
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From Statistical Model Checking to Run-Time Monitoring Using a Bayesian Network Approach
Jaeger, M., Larsen, K. G. & Tibo, A., 2020, Runtime Verification - 20th International Conference, RV 2020, Proceedings. Deshmukh, J. & Nickovic, D. (eds.). Springer Science+Business Media, p. 517-535 19 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12399 LNCS).Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
Open AccessFile61 Downloads (Pure)
Datasets
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Code and data for construction of a network architecture for Multi-Multi-Instance learning
Jaeger, M. (Creator), Frasconi, P. (Creator) & Tibo, A. (Creator), Figshare, 2017
DOI: 10.6084/m9.figshare.5442451.v1, https://doi.org/10.6084%2Fm9.figshare.5442451.v1
Dataset
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Code and data for construction of a network architecture for Multi-Multi-Instance learning
Tibo, A. (Creator), Frasconi, P. (Creator) & Jaeger, M. (Creator), Figshare, 2017
DOI: 10.6084/m9.figshare.5442451, https://figshare.com/articles/Code_and_data_for_construction_of_a_network_architecture_for_Multi-Multi-Instance_learning/5442451
Dataset