13 citations · 15 across the 3 of their papers we have counts for
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stat.ML2019★ 2 cited
Variational Characterizations of Local Entropy and Heat Regularization in Deep Learning
Nicolas Garcia Trillos, Zach Kaplan, Daniel Sanz-Alonso
The aim of this paper is to provide new theoretical and computational understanding on two loss regularizations employed in deep learning, known as local entropy and heat regulariz…
stat.ML2017★ 13 cited
On the Consistency of Graph-based Bayesian Learning and the Scalability of Sampling Algorithms
Nicolas Garcia Trillos, Zachary Kaplan, Thabo Samakhoana +1
A popular approach to semi-supervised learning proceeds by endowing the input data with a graph structure in order to extract geometric information and incorporate it into a Bayesi…