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Danica J. Sutherland
Danica J. Sutherland
University of British Columbia + Amii
Verified email at cs.ubc.ca - Homepage
Title
Cited by
Cited by
Year
Demystifying MMD GANs
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
International Conference on Learning Representations, 2018
16032018
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
9302021
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
2322017
On the error of random Fourier features
DJ Sutherland, J Schneider
Uncertainty in Artificial Intelligence, 2015
2232015
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
2042020
Does invariant risk minimization capture invariance?
P Kamath, A Tangella, D Sutherland, N Srebro
International Conference on Artificial Intelligence and Statistics, 4069-4077, 2021
1272021
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
1212015
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
Advances in neural information processing systems, 6700-6710, 2018
1042018
Exphormer: Sparse transformers for graphs
H Shirzad, A Velingker, B Venkatachalam, DJ Sutherland, AK Sinop
International Conference on Machine Learning, 31613-31632, 2023
1012023
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
902016
Learning deep kernels for exponential family densities
L Wenliang, DJ Sutherland, H Strathmann, A Gretton
International Conference on Machine Learning, 6737-6746, 2019
852019
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
782021
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
702021
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
702019
Nonparametric Kernel Estimators for Image Classification
B Póczos, L Xiong, DJ Sutherland, J Schneider
Computer Vision and Pattern Recognition, 2989-2996, 2012
642012
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
482013
Bayesian Approaches to Distribution Regression
HCL Law, DJ Sutherland, D Sejdinovic, S Flaxman
AISTATS, 2018
462018
Efficient and principled score estimation with Nyström kernel exponential families
DJ Sutherland, H Strathmann, M Arbel, A Gretton
AISTATS, 2018
412018
On Uniform Convergence and Low-Norm Interpolation Learning
L Zhou, DJ Sutherland, N Srebro
arXiv preprint arXiv:2006.05942, 2020
402020
Object discovery via contrastive learning for weakly supervised object detection
J Seo, W Bae, DJ Sutherland, J Noh, D Kim
European conference on computer vision, 312-329, 2022
332022
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