19 citations · 40 across the 5 of their papers we have counts for
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math.NA2020★ 1 cited
-order Tensor Products with Invertible Linear Transforms
Jun Han
This paper studies the issues about tensors. Three typical kinds of tensor decomposition are mentioned. Among these decompositions, the t-SVD is proposed in this decade. Different…
cs.LG2020★ 1 cited
Scalable Approximate Inference and Some Applications
Jun Han
Approximate inference in probability models is a fundamental task in machine learning. Approximate inference provides powerful tools to Bayesian reasoning, decision making, and Bay…
cs.LG2020★ 3 cited
Stein Variational Inference for Discrete Distributions
Jun Han, Fan Ding, Xianglong Liu +3
Gradient-based approximate inference methods, such as Stein variational gradient descent (SVGD), provide simple and general-purpose inference engines for differentiable continuous…