162 citations · 579 across the 17 of their papers we have counts for
Showing 2018 · stat.MLShow all
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stat.ML2018★ 10 cited
Learning deep kernels for exponential family densities
Li Wenliang, Danica J. Sutherland, Heiko Strathmann +1
The kernel exponential family is a rich class of distributions, which can be fit efficiently and with statistical guarantees by score matching. Being required to choose a priori a…
stat.ML2018★ 11 cited
Scalable Gaussian Processes on Discrete Domains
Vincent Fortuin, Gideon Dresdner, Heiko Strathmann +1
Kernel methods on discrete domains have shown great promise for many challenging data types, for instance, biological sequence data and molecular structure data. Scalable kernel me…