Gal Elidan

Cited by

	All	Since 2015
Citations	3510	1183
h-index	22	17
i10-index	35	24

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Co-authors

Nir FriedmanProfessor of Computer Science and Life Sciences, Hebrew UniversityVerified email at mail.huji.ac.il
Daphne KollerCEO and Founder, insitroVerified email at insitro.com
Geremy HeitzGoogle Inc.Verified email at google.com
Ian McGrawGoogle Inc.Verified email at google.com
Ami WieselHebrew University of Jerusalem, IsraelVerified email at mail.huji.ac.il
Stephen GouldAustralian National UniversityVerified email at anu.edu.au
Ariel JaimovichPostdoc in Biochemistry, Stanford universityVerified email at stanford.edu
Elad EbanGoogleVerified email at google.com
Tommy KaplanProfessor of Computer Science and Computational Biology, The Hebrew UniversityVerified email at cs.huji.ac.il
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
Pieter AbbeelUC Berkeley | Covariant.AIVerified email at cs.berkeley.edu
Gal ChechikBar Ilan University, NVIDIAVerified email at biu.ac.il
Mark HorowitzProfessor of Electrical Engineering and Computer ScienceVerified email at ee.stanford.edu
Iftach NachmanAssistant professor of biology, Tel Aviv UniversityVerified email at tauex.tau.ac.il
Ofer MeshiResearch Scientist at GoogleVerified email at google.com
Amir GlobersonTel Aviv UniversityVerified email at post.tau.ac.il
John DuchiAssistant Professor of Statistics and Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Daniel TarlowResearch Scientist, Google Brain - MontrealVerified email at cs.toronto.edu
Israel NelkenHebrew UniversityVerified email at mail.huji.ac.il
Roi LivniTel Aviv UniversityVerified email at tauex.tau.ac.il

Gal Elidan

Hebrew University / Google

Verified email at huji.ac.il - Homepage

Machine Learning Graphical Models Structure Learning Copulas


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Inferring subnetworks from perturbed expression profiles D Pe’er, A Regev, G Elidan, N Friedman Bioinformatics 17 (suppl_1), S215-S224, 2001	716	2001
Multi-class segmentation with relative location prior S Gould, J Rodgers, D Cohen, G Elidan, D Koller International Journal of Computer Vision 80 (3), 300-316, 2008	444	2008
Residual belief propagation: Informed scheduling for asynchronous message passing G Elidan, I McGraw, D Koller arXiv preprint arXiv:1206.6837, 2012	322	2012
Modeling dependencies in protein-DNA binding sites Y Barash, G Elidan, N Friedman, T Kaplan Proceedings of the seventh annual international conference on Research in …, 2003	296	2003
Markov random field based automatic image alignment for electron tomography F Amat, F Moussavi, LR Comolli, G Elidan, KH Downing, M Horowitz Journal of structural biology 161 (3), 260-275, 2008	142	2008
Discovering hidden variables: A structure-based approach G Elidan, N Lotner, N Friedman, D Koller Advances in Neural Information Processing Systems, 479-485, 2001	141	2001
Max-margin classification of data with absent features G Chechik, G Heitz, G Elidan, P Abbeel, D Koller The Journal of Machine Learning Research 9, 1-21, 2008	121	2008
Max-margin classification of data with absent features G Chechik, G Heitz, G Elidan, P Abbeel, D Koller Journal of Machine Learning Research 9 (Jan), 1-21, 2008	121	2008
Learning hidden variable networks: The information bottleneck approach G Elidan, N Friedman Journal of Machine Learning Research 6 (Jan), 81-127, 2005	115	2005
Copula bayesian networks G Elidan Advances in neural information processing systems, 559-567, 2010	113	2010
Data perturbation for escaping local maxima in learning G Elidan, M Ninio, N Friedman, D Schuurmans AAAI/IAAI, 132-139, 2002	99	2002
Using combinatorial optimization within max-product belief propagation D Tarlow, G Elidan, D Koller, JC Duchi Advances in neural information processing systems 19, 369-376, 2006	90	2006
Learning the dimensionality of hidden variables G Elidan, N Friedman arXiv preprint arXiv:1301.2269, 2013	85	2013
Towards an integrated protein–protein interaction network: A relational Markov network approach A Jaimovich, G Elidan, H Margalit, N Friedman Journal of Computational Biology 13 (2), 145-164, 2006	77	2006
Copulas in machine learning G Elidan Copulae in mathematical and quantitative finance, 39-60, 2013	74	2013
Learning bounded treewidth Bayesian networks G Elidan, S Gould Journal of Machine Learning Research 9 (Dec), 2699-2731, 2008	70	2008
Shape-based object localization for descriptive classification G Heitz, G Elidan, B Packer, D Koller Advances in Neural Information Processing Systems 21, 633-640, 2008	62	2008
Scalable learning of non-decomposable objectives E Eban, M Schain, A Mackey, A Gordon, R Rifkin, G Elidan Artificial intelligence and statistics, 832-840, 2017	51	2017
" Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks. G Elidan, I Nachman, N Friedman Journal of Machine Learning Research 8 (8), 2007	51	2007
Learning object shape: From drawings to images G Elidan, G Heitz, D Koller 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006	46	2006

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