Modeling Documents with Deep Boltzmann Machines

26 September 2013

Papers citing "Modeling Documents with Deep Boltzmann Machines"

10 / 10 papers shown

Title
MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model Md Abrar Jahin Asef Shahriar Md Al Amin AI4TS 28 4 0 24 May 2024
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley BDL AI4CE 11 8 0 26 Jul 2021
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick Mehdi Rezaee Francis Ferraro BDL DRL 17 27 0 22 Oct 2020
Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference Hao Zhang Bo Chen Yulai Cong D. Guo Hongwei Liu Mingyuan Zhou BDL 16 27 0 15 Jun 2020
Multi-local Collaborative AutoEncoder Jielei Chu Hongjun Wang Jing Liu Zhiguo Gong Tianrui Li BDL 13 9 0 12 Jun 2019
Modeling Activity Tracker Data Using Deep Boltzmann Machines M. Treppner S. Lenz Harald Binder D. Zöller 13 1 0 28 Feb 2018
Regularization for Unsupervised Deep Neural Nets Baiyang Wang Diego Klabjan BDL 15 25 0 15 Aug 2016
Learning from LDA using Deep Neural Networks Dongxu Zhang Tianyi Luo Dong Wang Rong Liu BDL 16 23 0 05 Aug 2015
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks Kai Sheng Tai R. Socher Christopher D. Manning AIMat 24 3,111 0 28 Feb 2015
Priors for Random Count Matrices Derived from a Family of Negative Binomial Processes Mingyuan Zhou Oscar Hernan Madrid Padilla James G. Scott 53 29 0 12 Apr 2014