Publikationen von J Mooij
Alle Typen
Zeitschriftenartikel (4)
1.
Zeitschriftenartikel
182-183, S. 1 - 31 (2012)
Information-geometric approach to inferring causal directions. Artificial Intelligence 2.
Zeitschriftenartikel
23 (1), S. 160 - 182 (2011)
A graphical model framework for decoding in the visual ERP-based BCI speller. Neural computation 3.
Zeitschriftenartikel
11, S. 2169 - 2173 (2010)
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models. The Journal of Machine Learning Research 4.
Zeitschriftenartikel
7 (3), S. 587 - 591 (2010)
Remote Sensing Feature Selection by Kernel Dependence Estimation. IEEE Geoscience and Remote Sensing Letters Konferenzbeitrag (11)
5.
Konferenzbeitrag
On causal and anticausal learning. In: 29th International Conference on Machine Learning (ICML 2012), S. 1255 - 1262 (Hg. Langford, J.; Pineau, J.). 29th International Conference on Machine Learning (ICML 2012), Edinburgh, UK. International Machine Learning Society, Madison, WI, USA (2012)
6.
Konferenzbeitrag
On Causal Discovery with Cyclic Additive Noise Models. In: Advances in Neural Information Processing Systems 24, S. 639 - 647 (Hg. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira, F.; Weinberger, K.). Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain. Curran, Red Hook, NY, USA (2012)
7.
Konferenzbeitrag
Efficient inference in matrix-variate Gaussian models with iid observation noise. In: Advances in Neural Information Processing Systems 24, S. 630 - 638 (Hg. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira, F.; Weinberger, K.). Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain. Curran, Red Hook, NY, USA (2012)
8.
Konferenzbeitrag
Identifiability of causal graphs using functional models. In: 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), S. 589 - 598 (Hg. Cozman, F.; Pfeffer, A.). 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), Barcelona, Spain. AUAI Press, Corvallis, OR, USA (2011)
9.
Konferenzbeitrag
Probabilistic latent variable models for distinguishing between cause and effect. Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Vancouver, BC, Canada, 06. Dezember 2010 - 11. Dezember 2010. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, S. 1687 - 1695 (2011)
10.
Konferenzbeitrag
Inferring deterministic causal relations. In: 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), S. 143 - 150 (Hg. Grünwald, P.; Spirtes, P.). 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, CA, USA, 08. Juli 2010 - 11. Juli 2010. AUAI Press, Corvallis, OR, USA (2010)
11.
Konferenzbeitrag
6, S. 147 - 156 (2010)
Distinguishing between cause and effect. NIPS 2008 Workshop: Causality: Objectives and Assessment, Whistler, BC, Canada, 12. Dezember 2008. JMLR Workshop and Conference Proceedings 12.
Konferenzbeitrag
Nonlinear causal discovery with additive noise models. In: Advances in neural information processing systems 21, S. 689 - 696 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)
13.
Konferenzbeitrag
Identifying confounders using additive noise models. In: 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009), S. 249 - 257 (Hg. Bilmes, N.; Ng, A.; McAllester, D.). 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009), Montréal, Canada, 18. Juni 2009 - 21. Juni 2009. AUAI Press, Corvallis, OR, USA (2009)
14.
Konferenzbeitrag
Regression by dependence minimization and its application to causal inference in additive noise models. In: ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, S. 745 - 752 (Hg. Danyluk, A.; Bottou, L.; Littman, M.). 26th International Conference on Machine Learning (ICML 2009), Montreal, Canada, 14. Juni 2009 - 18. Juni 2009. ACM Press, New York, NY, USA (2009)
15.
Konferenzbeitrag
Bounds on marginal probability distributions. In: Advances in neural information processing systems 21, S. 1105 - 1112 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)
Meeting Abstract (1)
16.
Meeting Abstract
09401, S. 10 (Hg. Janzing, D.; Lauritzen, B.; Schölkopf, B.). Dagstuhl Seminar: Machine learning approaches to statistical dependences and causality, Schloss Dagstuhl, Germany, 27. September 2009 - 02. Oktober 2009. Schloss Dagstuhl, Leibniz-Zentrum für Informatik, Wadern (2009)
Additive noise models for causal inference. In Dagstuhl Reports, Vortrag (1)
17.
Vortrag
libDAI. NIPS 2008 Workshop: Machine Learning Open-Source Software, Whistler, BC, Canada (2008)