Daniel M. Roy - Google Scholar Citations

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Co-authors

Joshua B. TenenbaumMITVerified email at mit.edu
Gintare Karolina DziugaiteResearch Scientist, Element AIVerified email at elementai.com
Vikash K. MansinghkaMIT, Probabilistic Computing ProjectVerified email at mit.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
martin rinardMITVerified email at lcs.mit.edu
Noah D. GoodmanStanford UniversityVerified email at stanford.edu
Cameron E. FreerResearch Scientist, MITVerified email at math.mit.edu
Balaji LakshminarayananResearch Scientist at Google DeepMindVerified email at google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Cristian CadarImperial College LondonVerified email at imperial.ac.uk
Nate AckermanHarvard UniversityVerified email at math.harvard.edu
Peter OrbanzColumbia UniversityVerified email at stat.columbia.edu
Victor VeitchColumbia UniversityVerified email at columbia.edu
James Robert LloydPhD from Machine Learning Group, Cambridge UniversityVerified email at cam.ac.uk
David SontagAssociate Professor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandVerified email at umiacs.umd.edu
Sasa MisailovicUniversity of Illinois at Urbana–ChampaignVerified email at illinois.edu
Leslie KaelblingVerified email at csail.mit.edu
David WingateAssistant professor of Computer Science, Brigham Young UniversityVerified email at cs.byu.edu
Jonathan HugginsPostdoctoral Research Fellow, HarvardVerified email at mit.edu

Daniel M. Roy

Assistant Professor of Statistics, University of Toronto

Verified email at utstat.toronto.edu - Homepage

Statistics Theoretical Computer Science Probability Machine Learning Artificial Intelligence


Title	Cited by	Year
Church: a language for generative models ND Goodman, VK Mansinghka, D Roy, K Bonawitz, JB Tenenbaum Uncertainty in Artificial Intelligence 22, 23, 2008	676*	2008
Enhancing server availability and security through failure-oblivious computing M Rinard, C Cadar, D Dumitran, DM Roy, T Leu, WS Beebee Jr Proceedings of the 6th conference on Symposium on Opearting Systems Design …, 2004	412	2004
Training generative neural networks via maximum mean discrepancy optimization GK Dziugaite, DM Roy, Z Ghahramani arXiv preprint arXiv:1505.03906, 2015	220	2015
Bayesian models of graphs, arrays and other exchangeable random structures P Orbanz, DM Roy IEEE transactions on pattern analysis and machine intelligence 37 (2), 437-461, 2014	150	2014
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data GK Dziugaite, DM Roy arXiv preprint arXiv:1703.11008, 2017	140	2017
A dynamic technique for eliminating buffer overflow vulnerabilities (and other memory errors) M Rinard, C Cadar, D Dumitran, DM Roy, T Leu 20th Annual Computer Security Applications Conference, 82-90, 2004	127	2004
Bayesian agglomerative clustering with coalescents YW Teh, H Daumé III, D Roy Arxiv preprint arXiv:0907.0781, 2009	109	2009
Mondrian forests: Efficient online random forests B Lakshminarayanan, DM Roy, YW Teh Advances in neural information processing systems, 3140-3148, 2014	108	2014
Complexity of Inference in Latent Dirichlet Allocation D Sontag, DM Roy	108*
The Mondrian process DM Roy, YW Teh Adv. in Neural Inform. Processing Syst 21, 27, 2009	105	2009
Probabilistically accurate program transformations S Misailovic, D Roy, M Rinard Static Analysis, 316-333, 2011	98	2011
Random function priors for exchangeable arrays with applications to graphs and relational data J Lloyd, P Orbanz, Z Ghahramani, DM Roy Advances in Neural Information Processing Systems, 998-1006, 2012	87	2012
A study of the effect of jpg compression on adversarial images GK Dziugaite, Z Ghahramani, DM Roy arXiv preprint arXiv:1608.00853, 2016	86	2016
Learning annotated hierarchies from relational data DM Roy, C Kemp, VK Mansinghka, JB Tenenbaum Advances in neural information processing systems, 1185-1192, 2007	61	2007
The class of random graphs arising from exchangeable random measures V Veitch, DM Roy arXiv preprint arXiv:1512.03099, 2015	56	2015
Noncomputable conditional distributions NL Ackerman, CE Freer, DM Roy 2011 IEEE 26th Annual Symposium on Logic in Computer Science, 107-116, 2011	48	2011
Efficient Bayesian Task-Level Transfer Learning. DM Roy, LP Kaelbling IJCAI 7, 2599-2604, 2007	45	2007
Neural network matrix factorization GK Dziugaite, DM Roy arXiv preprint arXiv:1511.06443, 2015	42	2015
Computable de Finetti measures CE Freer, DM Roy Annals of Pure and Applied Logic, 2011	40*	2011
Computability, inference and modeling in probabilistic programming DM Roy Massachusetts Institute of Technology, 2011	27	2011

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