| Detecting and quantifying causal associations in large nonlinear time series datasets J Runge, P Nowack, M Kretschmer, S Flaxman, D Sejdinovic Science Advances 5 (11), eaau4996, 2019 | 884 | 2019 |
| Optimal kernel choice for large-scale two-sample tests A Gretton, D Sejdinovic, H Strathmann, S Balakrishnan, M Pontil, ... Advances in Neural Information Processing Systems 25, 1214-1222, 2012 | 842 | 2012 |
| Equivalence of distance-based and RKHS-based statistics in hypothesis testing D Sejdinovic, B Sriperumbudur, A Gretton, K Fukumizu The Annals of Statistics 41 (5), 2263–2291, 2013 | 816 | 2013 |
| Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences M Kanagawa, P Hennig, D Sejdinovic, BK Sriperumbudur arXiv preprint arXiv:1807.02582, 2018 | 415 | 2018 |
| Unrepresentative big surveys significantly overestimated US vaccine uptake V Bradley, S Kuriwaki, M Isakov, D Sejdinovic, XL Meng, S Flaxman Nature, 2021 | 252 | 2021 |
| Expanding window fountain codes for unequal error protection D Sejdinovic, D Vukobratovic, A Doufexi, V Senk, R Piechocki Communications, IEEE Transactions on 57 (9), 2510-2516, 2009 | 241 | 2009 |
| Expanding window fountain codes for unequal error protection D Sejdinovic, D Vukobratovic, A Doufexi, V Senk, R Piechocki Asilomar Conference on Signals, Systems and Computers, 1020–1024, 2007 | 241 | 2007 |
| Probabilistic Integration: A Role in Statistical Computation? FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic Statistical Science 34 (1), 1-22, 2019 | 216* | 2019 |
| Fast two-sample testing with analytic representations of probability measures KP Chwialkowski, A Ramdas, D Sejdinovic, A Gretton Advances in Neural Information Processing Systems 28, 1981-1989, 2015 | 184 | 2015 |
| Scalable video multicast using expanding window fountain codes D Vukobratovic, V Stankovic, D Sejdinovic, L Stankovic, Z Xiong IEEE Transactions on Multimedia 11 (6), 1094-1104, 2009 | 173 | 2009 |
| Towards a Unified Analysis of Random Fourier Features Z Li, JF Ton, D Oglic, D Sejdinovic International Conference on Machine Learning, 3905-3914, 2019 | 154 | 2019 |
| Large-scale kernel methods for independence testing Q Zhang, S Filippi, A Gretton, D Sejdinovic Statistics and Computing 28 (1), 113–130, 2018 | 146 | 2018 |
| K2-ABC: Approximate Bayesian Computation with Kernel Embeddings M Park, W Jitkrittum, D Sejdinovic AISTATS, 2015 | 117 | 2015 |
| Hamiltonian variational auto-encoder AL Caterini, A Doucet, D Sejdinovic Advances in Neural Information Processing Systems 31, 8167-8177, 2018 | 111 | 2018 |
| Note on noisy group testing: asymptotic bounds and belief propagation reconstruction D Sejdinovic, O Johnson Proc. 48th Annual Allerton 2010 Conf. on Communication, Control and …, 2010 | 101 | 2010 |
| Gradient-free Hamiltonian Monte Carlo with efficient kernel exponential families H Strathmann, D Sejdinovic, S Livingstone, Z Szabo, A Gretton Advances in Neural Information Processing Systems 28, 955-963, 2015 | 94 | 2015 |
| Temporal structure in associative retrieval Z Kurth-Nelson, G Barnes, D Sejdinovic, R Dolan, P Dayan Elife 4, e04919, 2015 | 88 | 2015 |
| Machine learning enables completely automatic tuning of a quantum device faster than human experts H Moon, DT Lennon, J Kirkpatrick, NM van Esbroeck, LC Camenzind, ... Nature communications 11 (1), 4161, 2020 | 84 | 2020 |
| AND-OR tree analysis of distributed LT codes D Sejdinovic, RJ Piechocki, A Doufexi IEEE Information Theory Workshop on Networking and Information Theory (ITW …, 2009 | 78 | 2009 |
| A wild bootstrap for degenerate kernel tests KP Chwialkowski, D Sejdinovic, A Gretton Advances in neural information processing systems 27, 3608-3616, 2014 | 75 | 2014 |
Arthur GrettonGatsby Computational Neuroscience Unit and Google Deepmind在 gatsby.ucl.ac.uk 的电子邮件经过验证
