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researcher

Thomas Merkh

3 papers hereh-index 6244 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.IT1

identity via Semantic Scholar / OpenAlex

most citedStochastic Feedforward Neural Networks: Universal Approximation

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

cs.LG2020

Semi-supervised NMF Models for Topic Modeling in Learning Tasks

Jamie Haddock, Lara Kassab, Sixian Li +9

We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific d…

cs.LG2019★ 1 cited

Stochastic Feedforward Neural Networks: Universal Approximation

Thomas Merkh, Guido Montúfar

In this chapter we take a look at the universal approximation question for stochastic feedforward neural networks. In contrast to deterministic networks, which represent mappings f…

cs.IT2019

Factorized Mutual Information Maximization

Thomas Merkh, Guido Montúfar

We investigate the sets of joint probability distributions that maximize the average multi-information over a collection of margins. These functionals serve as proxies for maximizi…

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