kernel mean embedding

Reproducing kernel Hilbert C*-module and kernel mean embeddings JMLR 2021 A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control L4DC 2020 A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings NeurIPS 2020 Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise JMLR 2020 MATE: Plugging in Model Awareness to Task Embedding for Meta Learning NeurIPS 2020 Simulator Calibration under Covariate Shift with Kernels AISTATS 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 Bayesian Deconditional Kernel Mean Embeddings ICML 2019 Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference AISTATS 2019 Distribution-Based Semi-Supervised Learning for Activity Recognition AAAI 2019 MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means ICML 2019 Differentially Private Database Release via Kernel Mean Embeddings ICML 2018 Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions JMLR 2018 Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings ICML 2018 Minimax Estimation of Kernel Mean Embeddings JMLR 2017 Conditional Generative Moment-Matching Networks NeurIPS 2016 Consistent Kernel Mean Estimation for Functions of Random Variables NeurIPS 2016 The Randomized Causation Coefficient JMLR 2015 Towards a Learning Theory of Cause-Effect Inference ICML 2015 A Wild Bootstrap for Degenerate Kernel Tests NeurIPS 2014 Kernel Bayes' Rule NeurIPS 2011 Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions NeurIPS 2009