Motonobu Kanagawa
Title
Cited by
Cited by
Year
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
422018
Convergence guarantees for kernel-based quadrature rules in misspecified settings
M Kanagawa, BK Sriperumbudur, K Fukumizu
Advances in Neural Information Processing Systems, 3288-3296, 2016
312016
Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings
M Kanagawa, BK Sriperumbudur, K Fukumizu
Foundations of Computational Mathematics 20 (1), 155-194, 2020
232020
Filtering with state-observation examples via kernel monte carlo filter
M Kanagawa, Y Nishiyama, A Gretton, K Fukumizu
Neural computation 28 (2), 382-444, 2016
152016
Large sample analysis of the median heuristic
D Garreau, W Jitkrittum, M Kanagawa
arXiv preprint arXiv:1707.07269, 2017
132017
Monte Carlo filtering using kernel embedding of distributions
M Kanagawa, Y Nishiyama, A Gretton, K Fukumizu
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
102014
Convergence guarantees for adaptive Bayesian quadrature methods
M Kanagawa, P Hennig
Advances in Neural Information Processing Systems, 6237-6248, 2019
72019
Kernel recursive ABC: Point estimation with intractable likelihood
T Kajihara, M Kanagawa, K Yamazaki, K Fukumizu
arXiv preprint arXiv:1802.08404, 2018
52018
Unsupervised group matching with application to cross-lingual topic matching without alignment information
T Iwata, M Kanagawa, T Hirao, K Fukumizu
Data mining and knowledge discovery 31 (2), 350-370, 2017
42017
On the positivity and magnitudes of Bayesian quadrature weights
T Karvonen, M Kanagawa, S Särkkä
Statistics and Computing 29 (6), 1317-1333, 2019
32019
Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
Y Nishiyama, M Kanagawa, A Gretton, K Fukumizu
arXiv preprint arXiv:1409.5178, 2014
12014
Simulator Calibration under Covariate Shift with Kernels
K Kisamori, M Kanagawa, K Yamazaki
International Conference on Artificial Intelligence and Statistics, 1244-1253, 2020
2020
Model-based kernel sum rule: kernel Bayesian inference with probabilistic models
Y Nishiyama, M Kanagawa, A Gretton, K Fukumizu
Machine Learning, 1-34, 2020
2020
Model Selection for Simulator-based Statistical Models: A Kernel Approach
T Kajihara, M Kanagawa, Y Nakaguchi, K Khandelwal, K Fukumiziu
arXiv preprint arXiv:1902.02517, 2019
2019
Counterfactual Mean Embeddings
K Muandet, M Kanagawa, S Saengkyongam, S Marukatat
arXiv preprint arXiv:1805.08845, 2018
2018
Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference
K Muandet, M Kanagawa, S Saengkyongam, S Marukatat
arXiv, arXiv: 1805.08845, 2018
2018
Empirical representations of probability distributions via kernel mean embeddings
M Kanagawa
2016
Model-based Kernel Sum Rule with Applications to State Space Models
Y Nishiyama, M Kanagawa, A Gretton, K Fukumizu
Supplementary materials for “Convergence guarantees for kernel-based quadrature rules in misspecified settings”
M Kanagawa, BK Sriperumbudur, K Fukumizu
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