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Heiko Strathmann
Heiko Strathmann
Research Scientist at Deepmind
Verified email at deepmind.com - Homepage
Title
Cited by
Cited by
Year
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, 2012
8052012
A kernel test of goodness of fit
K Chwialkowski, H Strathmann, A Gretton
International conference on machine learning, 2606-2615, 2016
3542016
Generative models and model criticism via optimized maximum mean discrepancy
DJ Sutherland, HY Tung, H Strathmann, S De, A Ramdas, A Smola, ...
arXiv preprint arXiv:1611.04488, 2016
2202016
Som-vae: Interpretable discrete representation learning on time series
V Fortuin, M Hüser, F Locatello, H Strathmann, G Rätsch
arXiv preprint arXiv:1806.02199, 2018
1852018
On Russian roulette estimates for Bayesian inference with doubly-intractable likelihoods
AM Lyne, M Girolami, Y Atchadé, H Strathmann, D Simpson
156*2015
Nerf-vae: A geometry aware 3d scene generative model
AR Kosiorek, H Strathmann, D Zoran, P Moreno, R Schneider, S Mokrá, ...
International Conference on Machine Learning, 5742-5752, 2021
1342021
Soumyajit De, Aaditya Ramdas, Alex Smola, and Arthur Gretton. Generative models and model criticism via optimized maximum mean discrepancy
DJ Sutherland, HY Tung, H Strathmann
arXiv preprint arXiv:1611.04488 2, 2016
1302016
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, 2015
942015
Learning deep kernels for exponential family densities
L Wenliang, DJ Sutherland, H Strathmann, A Gretton
International Conference on Machine Learning, 6737-6746, 2019
812019
Kernel adaptive metropolis-hastings
D Sejdinovic, H Strathmann, ML Garcia, C Andrieu, A Gretton
International conference on machine learning, 1665-1673, 2014
612014
Efficient and principled score estimation with nyström kernel exponential families
DJ Sutherland, H Strathmann, M Arbel, A Gretton
International Conference on Artificial Intelligence and Statistics, 652-660, 2018
412018
Meta-learning mean functions for gaussian processes
V Fortuin, H Strathmann, G Rätsch
arXiv preprint arXiv:1901.08098, 2019
312019
Score-based diffusion meets annealed importance sampling
A Doucet, W Grathwohl, AG Matthews, H Strathmann
Advances in Neural Information Processing Systems 35, 21482-21494, 2022
292022
Escape from a Dominant HLA-B*15-Restricted CD8+ T Cell Response against Hepatitis C Virus Requires Compensatory Mutations outside the Epitope
M Ruhl, P Chhatwal, H Strathmann, T Kuntzen, D Bankwitz, K Skibbe, ...
Journal of virology 86 (2), 991-1000, 2012
262012
Sparse Gaussian processes on discrete domains
V Fortuin, G Dresdner, H Strathmann, G Rätsch
IEEE Access 9, 76750-76758, 2021
192021
Unbiased Bayes for big data: Paths of partial posteriors
H Strathmann, D Sejdinovic, M Girolami
arXiv preprint arXiv:1501.03326, 2015
192015
Neural variational gradient descent
LL di Langosco, V Fortuin, H Strathmann
arXiv preprint arXiv:2107.10731, 2021
172021
Persistent message passing
H Strathmann, M Barekatain, C Blundell, P Veličković
arXiv preprint arXiv:2103.01043, 2021
152021
Annealed importance sampling meets score matching
A Doucet, WS Grathwohl, AGG Matthews, H Strathmann
ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
92022
Kernel sequential Monte Carlo
I Schuster, H Strathmann, B Paige, D Sejdinovic
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
92017
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