Publications
Link to my
Profile -
Manfred Jaeger and Kim G. Larsen: Reinforcement learning for discretized Euclidean MDPs.
Proceedings of AISoLA 2024.
Pre-publication -
Francesco Ferrini, Antonio Longa, Andrea Passerini and Manfred Jaeger:
Meta-Path Learning for Multi-relational Graph Neural Networks.
The Second Learning on Graphs Conference, 2023.
Pre-publication -
Raffaele Pojer, Andrea Passerini and Manfred Jaeger:
Generalized Reasoning with Graph Neural Networks by Relational Bayesian Network Encodings.
The Second Learning on Graphs Conference, 2023.
Pre-publication - Manfred Jaeger, Antonio Longa, Steve Azzolin, Oliver Schulte and Andrea Passerini:
A Simple Latent Variable Model for Graph Learning and Inference.
The Second Learning on Graphs Conference, 2023.
Pre-publication - Parmis Naddaf, Erfaneh Mahmoudzaheh Ahmadi Nejad, Kiarash Zahirnia, Manfred Jaeger, and Oliver Schulte:
Joint Link Prediction Via Inference from a Model. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management.
Published paper -
Manfred Jaeger: Learning and Reasoning with Graph Data. Frontiers in Artificial Intelligence 6
Published paper -
Manfred Jaeger: Learning and Reasoning with Graph Data: Neural and Statistical-Relational Approaches.
International Research School in Artificial Intelligence in Bergen (AIB 2022) Open Access Series in Informatics (OASIcs), Vol. 99. 2022.
Published paper -
Manfred Jaeger: The AIM and EM Algorithms for Learning from Coarse Data. Journal of Machine Learning Research. 23(62):1−55, 2022.
Published paper -
Oliver Schulte, Parmis Naddaf, Xia Hu and Manfred Jaeger: Deep Variational Inference for Inductive Link Prediction. Deep Learning on Graphs: Method and Applications (DLG-AAAI’22)
Published paper -
Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi, Andrea Passerini, and Manfred Jaeger: Learning Aggregation Functions.
International Joint Conference on Artificial Intelligence (IJCAI) 2021
[Preprint with supplementary material] -
Alessandro Tibo, Manfred Jaeger, and Kim G. Larsen:
A general framework for defining and optimizing robustness.
arXiv preprint 2006.11122, 2021
Paper on arXiv - Alessandro Tibo, Manfred Jaeger and Paolo Frasconi: Learning and Interpreting Multi-Multi-Instance Learning Networks. Journal of Machine Learning Research Vol. 21, 2020
Published paper -
Manfred Jaeger, Kim G. Larsen and Alessandro Tibo: From Statistical Model Checking to Run-Time Monitoring Using a Bayesian Network Approach International Conference on Runtime Verification (RV)2020
Published paper -
Manfred Jaeger and Oliver Schulte: A Complete Characterization of Projectivity for Statistical Relational Models.
International Joint Conference on Artificial Intelligence (IJCAI) 2020
[Proceedings version] [Extended Version with Appendix] -
Alessandro Tibo, Manfred Jaeger and Kim G. Larsen: A general framework for defining and optimizing robustness.
Preprint on ArXiv -
Manfred Jaeger, Giorgio Bacci, Giovanni Bacci, Kim Guldstrand Larsen, and Peter Gjøl Jensen:
Approximating Euclidean by Imprecise Markov Decision Processes
International Symposium On Leveraging Applications of Formal Methods, Verification and Validation (ISoLA) 2020
Preprint -
Jaeger, M., Jensen, P.G., Larsen, K.G., Legay, A., Sedwards, S. and Taankvist, J.H: Teaching Stratego to Play Ball: Optimal Synthesis for Continuous Space MDPs. International Symposium on Automated Technology for Verification and Analysis pp. 81-97, Springer, 2019.
Published Paper -
Manfred Jaeger, Marco Lippi, Giovanni Pellegrini, and Andrea Passerini: Counts-of-counts similarity for prediction and search in relational data.
Data Mining and Knowledge Discovery , 2019.
Published Paper -
M. Jaeger and O. Schulte: Inference, Learning, and Population Size: Projectivity for SRL Models.
Eighth International Workshop on Statistical Relational AI (StarAI) , 2018.
Published Paper -
L. Schiff, O. Ziv, M. Jaeger, and S. Schmid: NetSlicer: Automated and Traffic-Pattern Based Application Clustering in Datacenters. Proceedings of the 2018 Workshop on Big Data Analytics and Machine Learning for Data Communication Networks, pp. 21-26, ACM, 2018
Published Paper -
A. I. Baba, H. Lu, T.B. Pedersen, and M. Jaeger: Cleansing indoor RFID tracking data. In: Sigspatial Special, 9(1), 11-18, 2017.
Published Paper -
A. Tibo, P. Frasconi, and M. Jaeger: A network architecture for multi-multi-instance learning. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECMLPKDD) pp. 737-752, Springer, 2017.
Published Paper -
H. Mao, Y. Chen, M. Jaeger, T.D. Nielsen, K.G. Larsen, and B. Nielsen: Learning deterministic probabilistic automata from a model checking perspective. In: Machine Learning, 2016.
Published Paper -
A.I. Baba, M. Jaeger, H. Lu, T. B. Pedersen, W.-S. Ku, and X. Xie: Learning-Based Cleansing for Indoor RFID Data. In: Proceedings of the 2016 International Conference on Management of Data (SIGMOD'16), pp. 925-936. ACM, 2016
Published Paper -
J. Jiang and M. Jaeger: Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis.
Working paper, 2015.
Preprint on ArXiv -
J. Smets and M. Jaeger: Multiple Image Segmentation.
In: A. Fred, M. De Marsico and A. Tabbone (Eds.): Pattern Recognition Applications and Methods. Revised selected papers from ICPRAM 2014. Springer LNCS 9443, pp. 3-18, 2015.
Published Paper -
Manfred Jaeger: Lower Complexity Bounds for Lifted Inference. In: Theory and Practice of Logic Programming (TPLP). Vol. 15, pp. 246-263, 2015.
Published Paper, Preprint on ArXiv -
Manfred Jaeger: Probabilistic Logic and Relational Models. In: R. Alhajj and J. Rokne (Eds.) Encyclopedia of Social Network Analysis and Mining. pp. 1403-1416. Springer, 2014.
Published Article -
Manfred Jaeger, Hua Mao, Kim G. Larsen and Radu Mardare: Continuity Properties of Distances for Markov Processes.
In:Proc. of the 11th International Conference on Quantitative Evaluation of SysTems (QEST 2014)
LNCS Vol. 8657, pp. 297-312.
Preprint with proof appendix, Published Paper -
Jiuchuan Jiang and Manfred Jaeger: Community Detection for Multiplex Social Networks Based on Relational Bayesian Networks. In: Proc. of the 21st Int. Symposium on Foundations of Intelligent Systems (ISMIS-2014)
LNCS Vol. 8502, pp. 30-39.
Published Paper -
Jonathan Smets and Manfred Jaeger: Multiple Segmentation of Image Stacks. In:
Proc. of the 3rd International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014) pp. 5-13
Preprint, Published Paper -
Manfred Jaeger, Marco Lippi, Andrea Passerini, and Paolo Frasconi: Type Extension Trees for Feature Construction and Learning in
Relational Domains. In Artificial Intelligence, Vol. 204, pp. 30-55, 2013.
Preprint Published Article -
Manfred Jaeger: Identifiability of Model Properties in Over-Parameterized Model Classes. In:
Proc. of ECML-13 Springer LNAI 8190, pp. 112-127
Preprint, Published paper -
Hua Mao and Manfred Jaeger: Learning and Model-Checking Networks of I/O Automata.
In: Proceedings of the Fourth Asian Conference on Machine Learning (ACML).2012.
Published paper. -
Yingke Chen, Hua Mao, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, and Brian Nielsen:
Learning Markov models for stationary system behaviors. In: Proceedings of the 4th NASA Formal Methods Symposium (NFM). 2012.
Published paper. -
Manfred Jaeger and Guy Van den Broeck: Liftability of Probabilistic Inference: Upper and Lower Bounds.
In: Proceedings of the 2nd International Workshop on Statistical Relational AI . 2012.
Published paper. -
Manfred Jaeger: Factorial Clustering of Species Distribution Data (Extended Abstract).
3rd International Conference on Computational Sustainability .2012.
Paper -
Marco Lippi, Manfred Jaeger, Paolo Frasconi and Andrea Passerini: Relational information gain.
Machine Learning,
Vol. 83 No. 2, pp. 219-239, 2011.
Published Article -
Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, and Brian Nielsen:
Learning Probabilistic Automata for Model Checking. In: Proceedings of 8th International Conference
on Quantitative Evaluation of SysTems (QEST). 2011.
Published paper. -
Manfred Jaeger, Simon P. Lyager, Michael W. Vandborg, and Thomas
Wohlgemuth: Factorial Clustering with an Application to
Plant Distribution Data. In: Proceedings of the 2nd MultiClust Workshop: Discovering, Summarizing and Using
Multiple Clusterings. 2011.
Published paper -
Bernd Gutmann, Manfred Jaeger and Luc De Raedt:
Extending ProbLog with Continuous Distributions. In: Inductive Logic Programming.
Proceedings of the 20th International Conference. LNCS 6489, Springer 2011.
Published Paper -
Luc De Raedt, Manfred Jaeger, Sau Dan Lee and Heikki Mannila: A Theory of Inductive Query Answering. In:
Saso Dzeroski, Bart Goethals and Pance Panov (Eds.) Inductive Databases and Constraint-Based Data Mining .
Springer, 2010.
Published Article -
Manfred Jaeger: On fairness and randomness. Information and Computation Vol. 207(9), pp. 909-922, 2009
Preprint, Published Article -
Marco Lippi, Manfred Jaeger, Paolo Frasconi, and Andrea Passerini:
Relational Information Gain. In: Online Proceedings of the 19th International Conference on Inductive Logic Programming (ILP 2009)
Published Paper -
Manfred Jaeger: Model-Theoretic Expressivity Analysis. In: L. De Raedt, P. Frasconi, K. Kersting, S.Muggleton (Eds) Probabilistic Inductive Logic Programming. Springer Lecture Notes in Computer Science, Vol.4911, 2008.
Preprint, Published Article -
Paolo Frasconi, Manfred Jaeger, and Andrea Passerini: Feature Discovery with Type Extension Trees. In: Proceedings of
the 18th Int. Conf. on Inductive Logic Programming (ILP-08). Springer Lecture Notes in Computer Science Vol.5194.
2008.
Preprint Published Article -
Manfred Jaeger: Probabilistic-Logic Models: Reasoning and Learning with Relational Structures.
In:Proc. of the 10th Scandinavian Conference on Artificial Intelligence (extended abstract). 2008.
PDF -
Manfred Jaeger, Petr Lidman, and Juan L. Mateo: Comparative Evaluation of PL Languages and Systems.
In: Proceedings of Mining and Learning with Graphs (MLG-07). 2007.
Published paper -
Manfred Jaeger: Parameter Learning for Relational Bayesian Networks. In: Proceedings of ICML-07 .
2007.
Published paper -
Manfred Jaeger, Jens D. Nielsen, Tomi Silander: Learning Probabilistic Decision Graphs,
International Journal of Approximate Reasoning, 42:84-100,2006.
Abstract, Published Article, Preprint -
Mark Chavira, Adnan Darwiche, Manfred Jaeger: Compiling Relational Bayesian Networks for Exact Inference,
International Journal of Approximate Reasoning,
42:4-20,2006.
Abstract, Published Article -
Manfred Jaeger: Probabilistic Role Models and the Guarded Fragment,
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems,
Vol. 14(1):43-59, 2006
Abstract, Published Article -
Manfred Jaeger: Type Extension Trees: a Unified Framework for Relational Feature Construction. In: Proceedings of
ECML/PKDD workshop on Mining and Learning with Graphs (MLG-2006). 2006.
Published paper -
Manfred Jaeger: On Testing the Missing at Random Assumption. In: Proceedings of ECML-06. p. 671-678, 2006
Preprint Published Article -
Jens Dalgaard Nielsen and Manfred Jaeger: An Empirical Study of Efficiency and Accuracy of Probabilistic
Graphical Models. In: Proceedings of PGM-06
Published paper -
Manfred Jaeger: The AI&M Procedure for Learning from Incomplete Data. In: Proceedings of UAI-06, pp. 225-232, 2006.
Published Paper -
Manfred Jaeger, Kristian Kersting and Luc De Raedt: Expressivity Analysis for PL-Languages (position paper).
In: Online proceedings of SRL 2006, 2pp, 2006
Published Paper -
Manfred Jaeger: Importance Sampling on Relational Bayesian Networks. In L. De Raedt et al. ed.
Probabilistic, Logical and Relational Learning - Towards a Synthesis, Dagstuhl Seminar
Proceedings 05051, 2006.
Abstract, Paper -
Manfred Jaeger: Ignorability in Statistical and Probabilistic Inference.
Journal of Artificial Intelligence Research
24:889-917,2005.
Abstract, Published Article -
Manfred Jaeger: A Logic for Inductive Probabilistic Reasoning.
Synthese, 144: 181-248, 2005.
Abstract, Preprint (PDF), Published Article -
Manfred Jaeger: Ignorability for Categorical Data. The Annals of Statistics, 33(4):1964-1981, 2005.
Abstract, PDF -
Manfred Jaeger: A Representation Theorem and Applications to Measure Selection and Noninformative Priors.
International Journal of Approximate Reasoning, 38 (3):217-243, 2005
Abstract, Preprint(PDF), Published Article -
Manfred Jaeger: Probabilistic Decision Graphs -- Combining Verification and AI
Techniques for Probabilistic Inference. International
Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 12:19-42, 2004
Abstract, PDF -
Manfred Jaeger, Jens D. Nielsen, Tomi Silander: Learning Probabilistic Decision Graphs.
In: Proceedings of the second European workshop on probabilistic graphical models. pp.113-120. 2004.
Abstract, PDF -
Mark Chavira, Adnan Darwiche, Manfred Jaeger: Compiling Relational Bayesian Networks for Exact Inference.
In: Proceedings of the second European workshop on probabilistic graphical models. pp.49-56. 2004.
Abstract, PDF -
Manfred Jaeger: Probabilistic Role Models and the Guarded Fragment. In
Proceedings of IPMU-04. pp.235-242
Abstract, PDF -
Manfred Jaeger: Probabilistic Classifiers and the Concepts they Recognize. In Proceedings
of ICML 2003.
Abstract, PDF -
Manfred Jaeger: A Representation Theorem and Applications. In Proceedings
of ECSQARU 2003.
Abstract, PDF -
Manfred Jaeger: A Representation Theorem and Applications to Measure Selection
and Noninformative Priors. Technical Report MPI-I-2003-2-002,
Max-Planck-Institut für Informatik, 2003.
Abstract , pdf -
Manfred Jaeger: Relational Bayesian Networks: a Survey. Electronic Transactions in Artificial
Intelligence, 6 , 2002.
Abstract, PDF -
Manfred Jaeger: Probabilistic Decision Graphs - Combining Verification and AI
Techniques for Probabilistic Inference. In: Proceedings of the
first European Workshop on Probabilistic Graphical Models, 2002.
Abstract, PDF - Luc de Raedt, Manfred Jaeger, Sau Dan Lee, Heikki Mannila: A
Theory of Inductive Query Answering. In Proceedings of ICDM'02.
Abstract, PDF -
Manfred Jaeger: Automatic Derivation of Probabilistic Inference Rules. International
Journal of Approximate Reasoning, 28(1):1-22, 2001
Abstract, Preprint(PDF) -
Manfred Jaeger: Complex Probabilistic Modeling with Recursive Relational Bayesian
Networks. Annals of Mathematics and Artificial Intelligence 32
(2001), pp. 179 - 220.
Abstract, Preprint(PDF) -
Manfred Jaeger: Constraints as Data: A New Perspective on Inferring
Probabilities. In: Proceedings of IJCAI-01.
Abstract, PDF -
Manfred Jaeger: On the Complexity of Inference about Probabilistic Relational
Models. Artificial Intelligence, 117 (2000), pp. 297-308.
Abstract, Preprint(PDF) -
Manfred Jaeger: Fairness, Computable Fairness and Randomness. In: Proceedings of
the 2nd International Workshop on Probabilistic Methods in Verification
(PROBMIV99). Technical Report CSR-99-8, School of Computer Science,
University of Birmingham (1999)
Abstract, PDF -
Manfred Jaeger: Measure Selection: Notions of Rationality and Representation
Independence. In: Proceedings of UAI-98.
Abstract, PDF - Manfred Jaeger: Convergence Results for Relational Bayesian Networks. In: Proceedings
of LICS-98.
Abstract, PDF - Manfred Jaeger: Reasoning About Infinite Random Structures with Relational
Bayesian Networks. In: Proceedings of KR-98, Morgan Kaufman,
San Francisco, CA. (1998)
Abstract, PDF - Manfred Jaeger: Relational Bayesian Networks. In: Proceedings of UAI-97,
Morgan Kaufmann, San Francisco, CA. (1997)
Abstract , PDF - Manfred Jaeger: Representation independence of nonmonotonic inference relations.
In: Proceedings of KR'96, Morgan Kaufmann, San Francisco, CA.
(1996)
Abstract, PDF - M. Jaeger, H. Mannila and E. Weydert: Data mining as selective
theory extraction in probabilistic logic. In: SIGMOD'96 Data Mining
Workshop
PDF - Manfred Jaeger: Minimum Cross-Entropy Reasoning: A Statistical Justification. In Proceedings
of IJCAI-95
Abstract , PDF - Manfred Jaeger: Default Reasoning about Probabilities. PhD. thesis,
Universität des Saarlandes , 1995.
Abstract, Thesis(527KB) - Manfred Jaeger: A Logic for Default Reasoning About Probabilities. In Proceedings
of the Tenth Conference on Uncertainty in Artificial Intelligence
(UAI-94), Morgan Kaufmann, San Francisco, CA.
Abstract, PDF - Manfred Jaeger: Probabilistic Reasoning in Terminological Logics. In J. Doyle, E.
Sandewall, and P. Torasso, editors, Principles of Knowledge
Representation and Reasoning: Proceedings of the Fourth International
Conference (KR94), Morgan Kaufmann, San Francisco, CA.
Abstract, PDF - A Probabilistic Extension of Terminological Logics. Technical Report MPI-I-94-208, Max-Planck-Institut für Informatik, 1994.
- Manfred Jaeger: Circumscription: Completeness reviewed. Artificial
Intelligence, 60 (1993), pp. 293-301.
Abstract, Preprint(PDF)