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 | 749 | 2012 |
A kernel test of goodness of fit K Chwialkowski, H Strathmann, A Gretton International conference on machine learning, 2606-2615, 2016 | 339 | 2016 |
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 | 211 | 2016 |
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 | 183 | 2018 |
On Russian roulette estimates for Bayesian inference with doubly-intractable likelihoods AM Lyne, M Girolami, Y Atchadé, H Strathmann, D Simpson | 153* | 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 | 128 | 2021 |
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 | 128 | 2016 |
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 | 90 | 2015 |
Learning deep kernels for exponential family densities L Wenliang, DJ Sutherland, H Strathmann, A Gretton International Conference on Machine Learning, 6737-6746, 2019 | 78 | 2019 |
Kernel adaptive metropolis-hastings D Sejdinovic, H Strathmann, ML Garcia, C Andrieu, A Gretton International conference on machine learning, 1665-1673, 2014 | 57 | 2014 |
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 | 41 | 2018 |
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 | 26 | 2012 |
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 | 25 | 2022 |
Meta-learning mean functions for gaussian processes V Fortuin, H Strathmann, G Rätsch arXiv preprint arXiv:1901.08098, 2019 | 25 | 2019 |
Sparse Gaussian processes on discrete domains V Fortuin, G Dresdner, H Strathmann, G Rätsch IEEE Access 9, 76750-76758, 2021 | 19 | 2021 |
Unbiased Bayes for big data: Paths of partial posteriors H Strathmann, D Sejdinovic, M Girolami arXiv preprint arXiv:1501.03326, 2015 | 19 | 2015 |
Neural variational gradient descent LL di Langosco, V Fortuin, H Strathmann arXiv preprint arXiv:2107.10731, 2021 | 17 | 2021 |
Persistent message passing H Strathmann, M Barekatain, C Blundell, P Veličković arXiv preprint arXiv:2103.01043, 2021 | 14 | 2021 |
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 | 8 | 2022 |
Kernel sequential Monte Carlo I Schuster, H Strathmann, B Paige, D Sejdinovic Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 7 | 2017 |