6 citations · 11 across the 4 of their papers we have counts for
4 papers
Bayesian Deconditional Kernel Mean Embeddings
Kelvin Hsu, Fabio Ramos
Conditional kernel mean embeddings form an attractive nonparametric framework for representing conditional means of functions, describing the observation processes for many complex…
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference
Kelvin Hsu, Fabio Ramos
In likelihood-free settings where likelihood evaluations are intractable, approximate Bayesian computation (ABC) addresses the formidable inference task to discover plausible param…
Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds
Kelvin Hsu, Richard Nock, Fabio Ramos
Conditional kernel mean embeddings are nonparametric models that encode conditional expectations in a reproducing kernel Hilbert space. While they provide a flexible and powerful f…
Chip-level CMP Modeling and Smart Dummy for HDP and Conformal CVD Films
George Yong Liu, Ray F. Zhang, Kelvin Hsu +1
Chip-level CMP modeling is investigated to obtain the post-CMP film profile thickness across a die from its design layout file and a few film deposition and CMP parameters. The wor…