Joris M. Mooij
Joris M. Mooij
Professor in Mathematical Statistics, Korteweg-de Vries Institute, University of Amsterdam (NL)
Geverifieerd e-mailadres voor uva.nl - Homepage
Titel
Geciteerd door
Geciteerd door
Jaar
MAGMA: Generalized Gene-Set Analysis of GWAS Data
CA de Leeuw, JM Mooij, T Heskes, D Posthuma
PLOS Computational Biology 11 (4), e1004219, 2015
9372015
Nonlinear causal discovery with additive noise models
PO Hoyer, D Janzing, JM Mooij, J Peters, B Schölkopf
Advances in neural information processing systems (NIPS*2008), 689-696, 2009
5452009
libDAI: A free and open source C++ library for discrete approximate inference in graphical models
JM Mooij
The Journal of Machine Learning Research 11, 2169-2173, 2010
3202010
Sufficient conditions for convergence of the sum–product algorithm
JM Mooij, HJ Kappen
IEEE Transactions on Information Theory 53 (12), 4422-4437, 2007
2652007
Distinguishing cause from effect using observational data: methods and benchmarks
JM Mooij, J Peters, D Janzing, J Zscheischler, B Schölkopf
The Journal of Machine Learning Research 17 (1), 1103-1204, 2016
2582016
Causal discovery with continuous additive noise models
J Peters, JM Mooij, D Janzing, B Schölkopf
The Journal of Machine Learning Research 15 (1), 2009-2053, 2014
2442014
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
arXiv preprint arXiv:1206.6471, 2012
2182012
Information-geometric approach to inferring causal directions
D Janzing, J Mooij, K Zhang, J Lemeire, J Zscheischler, P Daniušis, ...
Artificial Intelligence 182, 1-31, 2012
2052012
Causal effect inference with deep latent-variable models
C Louizos, U Shalit, JM Mooij, D Sontag, R Zemel, M Welling
Advances in Neural Information Processing Systems, 6446-6456, 2017
1642017
Inferring deterministic causal relations
P Daniušis, D Janzing, J Mooij, J Zscheischler, B Steudel, K Zhang, ...
Proceedings of the 26th Annual Conference on Uncertainty in Artificial …, 2010
1402010
Probabilistic latent variable models for distinguishing between cause and effect
O Stegle, D Janzing, K Zhang, JM Mooij, B Schölkopf
Advances in Neural Information Processing Systems (NIPS*2010), 1687-1695, 2010
1002010
Remote sensing feature selection by kernel dependence measures
G Camps-Valls, J Mooij, B Scholkopf
IEEE Geoscience and Remote Sensing Letters 7 (3), 587-591, 2010
972010
Regression by dependence minimization and its application to causal inference
J Mooij, D Janzing, J Peters, B Schölkopf
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
96*2009
Identifiability of causal graphs using functional models
J Peters, J Mooij, D Janzing, B Schölkopf
Proceedings of the 27th Annual Conference on Uncertainty in Artificial …, 2011
942011
Efficient inference in matrix-variate Gaussian models with iid observation noise
O Stegle, C Lippert, J Mooij, N Lawrence, K Borgwardt
Advances in Neural Information Processing Systems 23 (NIPS*2010), 1687--1695, 2011
872011
On causal discovery with cyclic additive noise models
JM Mooij, D Janzing, T Heskes, B Schölkopf
Advances in Neural Information Processing Systems (NIPS*2011), 639-647, 2011
702011
Learning sparse causal models is not NP-hard
T Claassen, J Mooij, T Heskes
Proceedings of the 29th Annual Conference on Uncertainty in Artificial …, 2013
692013
On the properties of the Bethe approximation and loopy belief propagation on binary networks
JM Mooij, HJ Kappen
Journal of Statistical Mechanics: Theory and Experiment 2005 (11), P11012, 2005
662005
Sufficient conditions for convergence of loopy belief propagation
J Mooij, H Kappen
Proceedings of the 21st Annual Conference on Uncertainty in Artificial …, 2005
64*2005
Methods for causal inference from gene perturbation experiments and validation
N Meinshausen, A Hauser, JM Mooij, J Peters, P Versteeg, P Bühlmann
Proceedings of the National Academy of Sciences 113 (27), 7361-7368, 2016
632016
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20