Danica J. Sutherland

Cited by

	All	Since 2016
Citations	1016	948
h-index	16	15
i10-index	18	18

340

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255

20122013201420152016201720182019202020214 7 11 36 62 96 158 244 335 50

Co-authors

Jeff SchneiderCarnegie Mellon UniversityVerified email at cs.cmu.edu
arthur grettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Heiko StrathmannResearch Scientist at DeepmindVerified email at ucl.ac.uk
Michael ArbelGatsby Computational Neuroscience Unit, UCLVerified email at ucl.ac.uk
Mikołaj BińkowskiResearch Scientist, DeepMindVerified email at google.com
Hy TracAssociate Professor, Department of Physics, McWilliams Center for Cosmology, Carnegie MellonVerified email at andrew.cmu.edu
Michelle NtampakaSpace Telescope Science InstituteVerified email at stsci.edu
Hsiao-Yu (Fish) TungCarnegie Mellon UniversityVerified email at cs.cmu.edu
Seth R. Flaxmansenior lecturer at Imperial College LondonVerified email at imperial.ac.uk
Sébastien FromenteauInstituto de Ciencias físicas, UNAMVerified email at turing-capital.com
Junier OlivaAssistant Professor, University of North CarolinaVerified email at cs.unc.edu
Aaditya RamdasStatistics and Machine Learning, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Alex SmolaAmazon Web ServicesVerified email at smola.org
Soumyajit DeBingAds, MicrosoftVerified email at microsoft.com
Dino SejdinovicUniversity of OxfordVerified email at stats.ox.ac.uk
Yifei MaApplied Scientist, Amazon.ComVerified email at amazon.com
Li Kevin WenliangGatsby Unit, University College LondonVerified email at gatsby.ucl.ac.uk
Ho Chung Leon LawDPhil in Statistics, University Of OxfordVerified email at spc.ox.ac.uk
Roman GarnettWashington University in St. LouisVerified email at wustl.edu

Danica J. Sutherland

University of British Columbia

Verified email at cs.ubc.ca - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Demystifying MMD GANs M Bińkowski, DJ Sutherland, M Arbel, A Gretton International Conference on Learning Representations, 2018	253	2018
Generative models and model criticism via optimized maximum mean discrepancy DJ Sutherland, HY Tung, H Strathmann, S De, A Ramdas, A Smola, ... International Conference on Learning Representations, 2017	132*	2017
On the error of random Fourier features DJ Sutherland, J Schneider Uncertainty in Artificial Intelligence, 2015	116	2015
A machine learning approach for dynamical mass measurements of galaxy clusters M Ntampaka, H Trac, DJ Sutherland, N Battaglia, B Póczos, J Schneider The Astrophysical Journal 803 (2), 50, 2015	71	2015
On gradient regularizers for MMD GANs M Arbel, DJ Sutherland, M Bińkowski, A Gretton Advances in neural information processing systems, 6700-6710, 2018	59	2018
Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning M Ntampaka, H Trac, DJ Sutherland, S Fromenteau, B Póczos, ... The Astrophysical Journal 831 (2), 2016	58	2016
Nonparametric Kernel Estimators for Image Classification B Póczos, L Xiong, DJ Sutherland, J Schneider Computer Vision and Pattern Recognition, 2989-2996, 2012	57	2012
Active learning and search on low-rank matrices DJ Sutherland, B Póczos, J Schneider Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	42	2013
Learning deep kernels for exponential family densities L Wenliang, DJ Sutherland, H Strathmann, A Gretton International Conference on Machine Learning, 6737-6746, 2019	30	2019
Bayesian Approaches to Distribution Regression HCL Law, DJ Sutherland, D Sejdinovic, S Flaxman AISTATS, 2018	28	2018
Kernels on sample sets via nonparametric divergence estimates DJ Sutherland, L Xiong, B Póczos, J Schneider arXiv preprint arXiv:1202.0302, 2012	25*	2012
Efficient and principled score estimation with Nyström kernel exponential families DJ Sutherland, H Strathmann, M Arbel, A Gretton AISTATS, 2018	21*	2018
Active pointillistic pattern search Y Ma, DJ Sutherland, R Garnett, J Schneider Artificial Intelligence and Statistics, 672-680, 2015	20	2015
The role of machine learning in the next decade of cosmology M Ntampaka, C Avestruz, S Boada, J Caldeira, J Cisewski-Kehe, ... arXiv preprint arXiv:1902.10159, 2019	19	2019
Understanding the 2016 US Presidential Election using ecological inference and distribution regression with census microdata S Flaxman, DJ Sutherland, YX Wang, YW Teh arXiv preprint arXiv:1611.03787, 2016	17	2016
Linear-time learning on distributions with approximate kernel embeddings DJ Sutherland, J Oliva, B Póczos, J Schneider Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016	16	2016
Learning Deep Kernels for Non-Parametric Two-Sample Tests F Liu, W Xu, J Lu, G Zhang, A Gretton, DJ Sutherland arXiv preprint arXiv:2002.09116, 2020	15	2020
Scalable, Flexible and Active Learning on Distributions DJ Sutherland Carnegie Mellon University, 2016	11	2016
Deep mean maps JB Oliva, DJ Sutherland, B Póczos, J Schneider arXiv preprint arXiv:1511.04150, 2015	9	2015
Unbiased estimators for the variance of MMD estimators DJ Sutherland arXiv preprint arXiv:1906.02104, 2019	6	2019

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