Stochastic Feedforward Neural Networks: Universal Approximation. - Thomas Merkh; Guido Montúfar (CoRR, 2019)

Semi-supervised NMF Models for Topic Modeling in Learning Tasks. - Jamie Haddock; Lara Kassab; Sixian Li; Alona Kryshchenko; Rachel Grotheer; Elena Sizikova; Chuntian Wang; Thomas Merkh; R. W. M. A. Madushani; Miju Ahn; Deanna Needell; Kathryn Leonard (CoRR, 2020)

Factorized mutual information maximization. - Thomas Merkh; Guido Montúfar (Kybernetika, 2020)

Semi-supervised Nonnegative Matrix Factorization for Document Classification. - Jamie Haddock; Lara Kassab; Sixian Li; Alona Kryshchenko; Rachel Grotheer; Elena Sizikova; Chuntian Wang; Thomas Merkh; R. W. M. A. Madushani; Miju Ahn; Deanna Needell; Kathryn Leonard (ACSCC, 2021)

Automatic Infectious Disease Classification Analysis with Concept Discovery. - Elena Sizikova; Joshua Vendrow; Xu Cao; Rachel Grotheer; Jamie Haddock; Lara Kassab; Alona Kryshchenko; Thomas Merkh; R. W. M. A. Madushani; Kenny Moise; Annie Ulichney; Huy V. Vo; et al. (CoRR, 2022)

Geometry of Linear Convolutional Networks. - Kathlén Kohn; Thomas Merkh; Guido Montúfar; Matthew Trager (SIAM J. Appl. Algebra Geom., 2022)