Murat Kocaoglu

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Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Karthikeyan ShanmugamResearch Scientist, Google Research IndiaVerified email at google.com
Sriram VishwanathUniversity of TexasVerified email at utexas.edu
Ozgur B. AkanUniversity of Cambridge, UK, and Koç University, TurkeyVerified email at cam.ac.uk
Kristjan GreenewaldResearch Scientist, MIT-IBM Watson AI Lab, IBM ResearchVerified email at ibm.com
Elias BareinboimColumbia UniversityVerified email at columbia.edu
Derya MalakEURECOM, Rensselaer Polytechnic InstituteVerified email at eurecom.fr
Spencer ComptonStanford UniversityVerified email at stanford.edu
Amin JaberPhD Student, Purdue UniversityVerified email at purdue.edu
Christopher SnyderPathology resident at Washington University in St. LouisVerified email at wustl.edu
Rajat SenGoogleVerified email at utexas.edu
Babak HassibiMose and Lilian S. Bohn Professor of Electrical EngineeringVerified email at caltech.edu
Sara MagliacaneUniversity of AmsterdamVerified email at uva.nl
Mahsa GhasemiAssistant Professor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
Qasim ElahiPhD. StudentVerified email at purdue.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinVerified email at utexas.edu
Lai WeiUnviversity of MichiganVerified email at umich.edu
Shiv SainiAdobe ResearchVerified email at adobe.com
Saurabh BagchiElectrical and Computer Engineering, Computer Science; Director Army A2I2 & NSF CHORUS; PurdueVerified email at purdue.edu
Subrata MitraAdobe ResearchVerified email at adobe.com

Murat Kocaoglu

Assistant Professor, School of ECE, Purdue University

Verified email at purdue.edu - Homepage

Causal Inference Machine Learning Information Theory


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Causalgan: Learning causal implicit generative models with adversarial training M Kocaoglu, C Snyder, AG Dimakis, S Vishwanath International Conference on Learning Representations (ICLR), 2018	306	2018
Learning causal graphs with small interventions K Shanmugam, M Kocaoglu, AG Dimakis, S Vishwanath Advances in Neural Information Processing Systems 28, 2015	114	2015
Causal discovery from soft interventions with unknown targets: Characterization and learning A Jaber, M Kocaoglu, K Shanmugam, E Bareinboim Advances in neural information processing systems 33, 9551-9561, 2020	104	2020
Experimental design for learning causal graphs with latent variables M Kocaoglu, K Shanmugam, E Bareinboim Advances in Neural Information Processing Systems 30, 2017	93	2017
Cost-optimal learning of causal graphs M Kocaoglu, A Dimakis, S Vishwanath International Conference on Machine Learning, 1875-1884, 2017	75	2017
Entropic causal inference M Kocaoglu, A Dimakis, S Vishwanath, B Hassibi Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	72	2017
Characterization and learning of causal graphs with latent variables from soft interventions M Kocaoglu, A Jaber, K Shanmugam, E Bareinboim Advances in Neural Information Processing Systems 32, 2019	62	2019
Root cause analysis of failures in microservices through causal discovery A Ikram, S Chakraborty, S Mitra, S Saini, S Bagchi, M Kocaoglu Advances in Neural Information Processing Systems 35, 31158-31170, 2022	57	2022
Contextual bandits with latent confounders: An nmf approach R Sen, K Shanmugam, M Kocaoglu, A Dimakis, S Shakkottai Artificial Intelligence and Statistics, 518-527, 2017	56	2017
Minimum energy channel codes for nanoscale wireless communications M Kocaoglu, OB Akan IEEE Transactions on Wireless Communications 12 (4), 1492-1500, 2013	56	2013
Experimental design for cost-aware learning of causal graphs E Lindgren, M Kocaoglu, AG Dimakis, S Vishwanath Advances in Neural Information Processing Systems 31, 2018	51	2018
Sample efficient active learning of causal trees K Greenewald, D Katz, K Shanmugam, S Magliacane, M Kocaoglu, ... Advances in Neural Information Processing Systems 32, 2019	48	2019
Active structure learning of causal DAGs via directed clique trees C Squires, S Magliacane, K Greenewald, D Katz, M Kocaoglu, ... Advances in Neural Information Processing Systems 33, 21500-21511, 2020	39	2020
Communication theoretic analysis of the synaptic channel for cortical neurons D Malak, M Kocaoglu, OB Akan Nano Communication Networks 4 (3), 131-141, 2013	27	2013
Fundamentals of green communications and computing: Modeling and simulation M Kocaoglu, D Malak, OB Akan Computer 45 (9), 40-46, 2012	27	2012
Minimum energy coding for wireless nanosensor networks M Kocaoglu, OB Akan 2012 Proceedings IEEE INFOCOM, 2826-2830, 2012	26	2012
Applications of common entropy for causal inference M Kocaoglu, S Shakkottai, AG Dimakis, C Caramanis, S Vishwanath Advances in neural information processing systems 33, 17514-17525, 2020	23	2020
Entropic causal inference: Identifiability and finite sample results S Compton, M Kocaoglu, K Greenewald, D Katz Advances in Neural Information Processing Systems 33, 14772-14782, 2020	16	2020
Entropic causality and greedy minimum entropy coupling M Kocaoglu, AG Dimakis, S Vishwanath, B Hassibi 2017 IEEE International Symposium on Information Theory (ISIT), 1465-1469, 2017	16	2017
Sparse polynomial learning and graph sketching M Kocaoglu, K Shanmugam, AG Dimakis, A Klivans Advances in Neural Information Processing Systems 27, 2014	16	2014

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