Kanagawa, Heishiro

9 publications

AISTATS 2025 Reinforcement Learning for Adaptive MCMC Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates

ICML 2023 A Kernel Stein Test of Goodness of Fit for Sequential Models Jerome Baum, Heishiro Kanagawa, Arthur Gretton

NeurIPS 2023 Stein $\Pi$-Importance Sampling Congye Wang, Ye Chen, Heishiro Kanagawa, Chris J Oates

NeurIPS 2021 Deep Proxy Causal Learning and Its Application to Confounded Bandit Policy Evaluation Liyuan Xu, Heishiro Kanagawa, Arthur Gretton

ICML 2020 Amortised Learning by Wake-Sleep Li Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani

UAI 2020 Testing Goodness of Fit of Conditional Density Models with Kernels Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf

NeurIPS 2018 Informative Features for Model Comparison Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton

ICML 2016 Gaussian Process Nonparametric Tensor Estimator and Its Minimax Optimality Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami

NeurIPS 2016 Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami