Dino Sejdinovic
Dino Sejdinovic
Professor of Statistical Machine Learning, University of Adelaide
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Optimal kernel choice for large-scale two-sample tests
A Gretton, BK Sriperumbudur, D Sejdinovic, H Strathmann, ...
Advances in Neural Information Processing Systems 25, 1214-1222, 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
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
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
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
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
Unrepresentative big surveys significantly overestimated US vaccine uptake
V Bradley, S Kuriwaki, M Isakov, D Sejdinovic, XL Meng, S Flaxman
Nature, 2021
Probabilistic Integration: A Role in Statistical Computation?
FX Briol, CJ Oates, M Girolami, MA Osborne, D Sejdinovic
Statistical Science 34 (1), 1-22, 2019
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
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
Towards a Unified Analysis of Random Fourier Features
Z Li, JF Ton, D Oglic, D Sejdinovic
International Conference on Machine Learning, 3905-3914, 2019
Large-scale kernel methods for independence testing
Q Zhang, S Filippi, A Gretton, D Sejdinovic
Statistics and Computing 28 (1), 113–130, 2018
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
M Park, W Jitkrittum, D Sejdinovic
Hamiltonian variational auto-encoder
AL Caterini, A Doucet, D Sejdinovic
Advances in Neural Information Processing Systems 31, 8167-8177, 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
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
Temporal structure in associative retrieval
Z Kurth-Nelson, G Barnes, D Sejdinovic, R Dolan, P Dayan
Elife 4, e04919, 2015
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
A wild bootstrap for degenerate kernel tests
KP Chwialkowski, D Sejdinovic, A Gretton
Advances in neural information processing systems 27, 3608-3616, 2014
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
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