Danica J. Sutherland

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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
Mikołaj BińkowskiResearch Scientist, DeepMindVerified email at google.com
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Heiko StrathmannResearch Scientist at DeepmindVerified email at deepmind.com
Lijia ZhouUniversity of ChicagoVerified email at uchicago.edu
Wonho BaeUniversity of British Columbia, VancouverVerified email at cs.ubc.ca
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
Feng Liu (he/him)Lecturer, University of Melbourne / Visiting Scientist, RIKEN-AIP / Visiting Fellow, UTS-AAIIVerified email at unimelb.edu.au
Wenkai XuPostdoc, Foundations of Machine Learning Systems group, Tuebingen AI CenterVerified email at uni-tuebingen.de
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
Hsiao-Yu (Fish) TungCarnegie Mellon UniversityVerified email at cs.cmu.edu
Soumyajit DeBingAds, MicrosoftVerified email at microsoft.com
Sébastien FromenteauInstituto de Ciencias físicas, UNAMVerified email at icf.unam.mx
Junier OlivaAssociate Professor, University of North CarolinaVerified email at cs.unc.edu

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	1472	2018
Pot: Python optimal transport R Flamary, N Courty, A Gramfort, MZ Alaya, A Boisbunon, S Chambon, ... Journal of Machine Learning Research 22 (78), 1-8, 2021	853	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	219	2017
On the error of random Fourier features DJ Sutherland, J Schneider Uncertainty in Artificial Intelligence, 2015	217	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	186	2020
Does invariant risk minimization capture invariance? P Kamath, A Tangella, D Sutherland, N Srebro International Conference on Artificial Intelligence and Statistics, 4069-4077, 2021	117	2021
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	112	2015
On gradient regularizers for MMD GANs M Arbel, DJ Sutherland, M Bińkowski, A Gretton Advances in neural information processing systems, 6700-6710, 2018	102	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	86	2016
Learning deep kernels for exponential family densities L Wenliang, DJ Sutherland, H Strathmann, A Gretton International Conference on Machine Learning, 6737-6746, 2019	81	2019
Exphormer: Sparse transformers for graphs H Shirzad, A Velingker, B Venkatachalam, DJ Sutherland, AK Sinop International Conference on Machine Learning, 31613-31632, 2023	72	2023
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	68	2021
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	67	2019
Nonparametric Kernel Estimators for Image Classification B Póczos, L Xiong, DJ Sutherland, J Schneider Computer Vision and Pattern Recognition, 2989-2996, 2012	64	2012
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	63	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	48	2013
Bayesian Approaches to Distribution Regression HCL Law, DJ Sutherland, D Sejdinovic, S Flaxman AISTATS, 2018	45	2018
Efficient and principled score estimation with Nyström kernel exponential families DJ Sutherland, H Strathmann, M Arbel, A Gretton AISTATS, 2018	41	2018
On Uniform Convergence and Low-Norm Interpolation Learning L Zhou, DJ Sutherland, N Srebro arXiv preprint arXiv:2006.05942, 2020	37	2020
Kernels on sample sets via nonparametric divergence estimates DJ Sutherland, L Xiong, B Póczos, J Schneider arXiv preprint arXiv:1202.0302, 2012	33*	2012

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