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Tue Herlau
Tue Herlau
Verified email at dtu.dk
Title
Cited by
Cited by
Year
Completely random measures for modelling block-structured sparse networks
T Herlau, MN Schmidt, M Mørup
Advances in Neural Information Processing Systems 29, 2016
552016
Infinite-degree-corrected stochastic block model
T Herlau, MN Schmidt, M Mørup
Physical review E 90 (3), 032819, 2014
282014
Detecting hierarchical structure in networks
T Herlau, M Mørup, MN Schmidt, LK Hansen
2012 3rd International Workshop on Cognitive Information Processing (CIP), 1-6, 2012
212012
Modeling temporal evolution and multiscale structure in networks
T Herlau, M Mørup, M Schmidt
International Conference on Machine Learning, 960-968, 2013
202013
Introduction to machine learning and data mining
T Herlau, MN Schmidt, M Mørup
Lecture notes of the course of the same name given at DTU (Technical …, 2016
162016
Comparing structural brain connectivity by the infinite relational model
KS Ambrosen, T Herlau, T Dyrby, MN Schmidt, M Mørup
2013 International Workshop on Pattern Recognition in Neuroimaging, 50-53, 2013
162013
Modelling dense relational data
T Herlau, M Mørup, MN Schmidt, LK Hansen
2012 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2012
162012
Cross-categorization of legal concepts across boundaries of legal systems: in consideration of inferential links
FK Glückstad, T Herlau, MN Schmidt, M Mørup
Artificial intelligence and law 22, 61-108, 2014
15*2014
Nonparametric Bayesian models of hierarchical structure in complex networks
MN Schmidt, T Herlau, M Mørup
arXiv preprint arXiv:1311.1033, 2013
112013
Advances in Neural Information Processing Systems
T Herlau, MN Schmidt, M Mørup, DD Lee, M Sugiyama, LU Von, I Guyon, ...
Curran Associates, Red Hook 29, 4260-4268, 2016
102016
Nonparametric statistical structuring of knowledge systems using binary feature matches
M Mørup, FK Glückstad, T Herlau, MN Schmidt
2014 IEEE International Workshop on Machine Learning for Signal Processing …, 2014
102014
Reinforcement learning of causal variables using mediation analysis
T Herlau, R Larsen
Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6910-6917, 2022
62022
Bayesian dropout
T Herlau, MN Schmidt, M Mørup
Procedia Computer Science 201, 771-776, 2022
62022
Analysis of conceptualization patterns across groups of people
FK Glückstad, T Herlau, MN Schmidt, M Mørup, R Rzepka, K Araki
2013 Conference on Technologies and Applications of Artificial Intelligence …, 2013
52013
Analysis of subjective conceptualizations towards collective concept modelling
FK Glückstad, T Herlau, MN Schmidt, M Mørup
人工知能学会全国大会論文集 第 27 回 (2013), 4C1IOS4b5-4C1IOS4b5, 2013
42013
Sequential decision making
T Herlau
Freely available online, 2024
32024
Causal variables from reinforcement learning using generalized Bellman equations
T Herlan
arXiv preprint arXiv:2010.15745, 2020
32020
Joint modelling of structural and functional brain networks
KW Andersen, T Herlau, M Mørup, MN Schmidt, KH Madsen, M Lyksborg, ...
2nd NIPS Workshop on Machine Learning and Interpretation in NeuroImaging …, 2012
32012
Moral reinforcement learning using actual causation
T Herlau
2022 2nd International Conference on Computer, Control and Robotics (ICCCR …, 2022
12022
Efficient inference of overlapping communities in complex networks
BØ Fruergaard, T Herlau
arXiv preprint arXiv:1411.7864, 2014
12014
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Articles 1–20