Danica J. Sutherland

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Citations	3384	3156
h-index	21	19
i10-index	33	32

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Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Jeff SchneiderCarnegie Mellon UniversityVerified email at cs.cmu.edu
Michael ArbelInria - Univ. Grenoble AlpesVerified email at inria.fr
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Heiko StrathmannResearch Scientist at DeepmindVerified email at deepmind.com
Mikołaj BińkowskiResearch Scientist, DeepMindVerified email at google.com
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
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
Lijia ZhouUniversity of ChicagoVerified email at uchicago.edu
Feng Liu (he/him)Lecturer, University of Melbourne / Visiting Scientist, RIKEN-AIP / Visiting Fellow, UTS-AAIIVerified email at unimelb.edu.au
Wenkai XuPostdoc, Department of Statistics, University of OxfordVerified email at stats.ox.ac.uk
Seth Flaxmanassociate professor at OxfordVerified email at cs.ox.ac.uk
Aaditya RamdasStatistics and Machine Learning, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Alex SmolaBoson AIVerified email at smola.org
Soumyajit DeBingAds, MicrosoftVerified email at microsoft.com
Sébastien FromenteauInstituto de Ciencias físicas, UNAMVerified email at icf.unam.mx
Junier OlivaAssistant Professor, University of North CarolinaVerified email at cs.unc.edu
Dino SejdinovicProfessor, University of AdelaideVerified email at adelaide.edu.au

Danica J. Sutherland

University of British Columbia + Amii

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	1045	2018
Pot: Python optimal transport R Flamary, N Courty, A Gramfort, MZ Alaya, A Boisbunon, S Chambon, ... The Journal of Machine Learning Research 22 (1), 3571-3578, 2021	584	2021
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	295*	2017
On the error of random Fourier features DJ Sutherland, J Schneider Uncertainty in Artificial Intelligence, 2015	197	2015
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	148	2020
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	102	2015
On gradient regularizers for MMD GANs M Arbel, DJ Sutherland, M Bińkowski, A Gretton Advances in neural information processing systems, 6700-6710, 2018	99	2018
Does invariant risk minimization capture invariance? P Kamath, A Tangella, D Sutherland, N Srebro International Conference on Artificial Intelligence and Statistics, 4069-4077, 2021	94	2021
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	80	2016
Learning deep kernels for exponential family densities L Wenliang, DJ Sutherland, H Strathmann, A Gretton International Conference on Machine Learning, 6737-6746, 2019	73	2019
Nonparametric Kernel Estimators for Image Classification B Póczos, L Xiong, DJ Sutherland, J Schneider Computer Vision and Pattern Recognition, 2989-2996, 2012	65	2012
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	63	2019
Self-supervised learning with kernel dependence maximization Y Li, R Pogodin, DJ Sutherland, A Gretton Advances in Neural Information Processing Systems 34, 15543-15556, 2021	49	2021
Uniform convergence of interpolators: Gaussian width, norm bounds and benign overfitting F Koehler, L Zhou, DJ Sutherland, N Srebro Advances in Neural Information Processing Systems 34, 20657-20668, 2021	48	2021
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	45	2013
Bayesian Approaches to Distribution Regression HCL Law, DJ Sutherland, D Sejdinovic, S Flaxman AISTATS, 2018	39	2018
Efficient and principled score estimation with Nyström kernel exponential families DJ Sutherland, H Strathmann, M Arbel, A Gretton AISTATS, 2018	37	2018
Kernels on sample sets via nonparametric divergence estimates DJ Sutherland, L Xiong, B Póczos, J Schneider arXiv preprint arXiv:1202.0302, 2012	32*	2012
On Uniform Convergence and Low-Norm Interpolation Learning L Zhou, DJ Sutherland, N Srebro arXiv preprint arXiv:2006.05942, 2020	31	2020
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	27	2016

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