Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations Honglak Lee Roger Grosse Rajesh Ranganath

Source URL: www.cs.toronto.edu

• Artificial intelligence
• Information
• Plasma physics
• Space plasmas
• OSI protocols
• Boltzmann machine
• Unsupervised learning
• Pattern recognition
• Data link layer
• Machine learning
• Neural networks
• Data

Cardinality Restricted Boltzmann Machines Kevin Swersky Daniel Tarlow Ilya Sutskever

Source URL: papers.nips.cc

• Networks
• Mathematics
• Applied mathematics
• Computational neuroscience
• Boltzmann machine
• Belief propagation
• Bayesian network
• Machine learning
• Sparse matrix
• Neural networks
• Statistics
• Graphical models

Learning to Disentangle Factors of Variation with Manifold Interaction Scott Reed REEDSCOT @ UMICH . EDU Kihyuk Sohn KIHYUKS @ UMICH . EDU

Source URL: www-personal.umich.edu

• Boltzmann machine
• Multivariate statistics
• Differential topology
• Differential geometry
• Manifold
• Nonlinear dimensionality reduction
• Partition function
• Object recognition
• Ludwig Boltzmann
• Statistics
• Topology
• Physics

The Recurrent Temporal Restricted Boltzmann Machine Ilya Sutskever, Geoffrey Hinton, and Graham Taylor University of Toronto {ilya, hinton, gwtaylor}@cs.utoronto.ca

Source URL: papers.nips.cc

• Neural networks
• Science
• Bayesian statistics
• Boltzmann machine
• Markov models
• Probability theory
• Hidden Markov model
• Belief propagation
• Information theory
• Statistics
• Graphical models
• Mathematics

The flip-the-state transition operator for restricted Boltzmann machines Kai Brügge, Asja Fischer & Christian Igel Machine Learning

Source URL: image.diku.dk

International Journal of Computer Vision manuscript No. (will be inserted by the editor) The Shape Boltzmann Machine A Strong Model of Object Shape S. M. Ali Eslami · Nicolas Heess

Source URL: arkitus.com

Gated Boltzmann Machine for Recognition under Occlusion Yichuan Tang Dept. of Computer Science, Univ. of Toronto 6 King’s College Rd.

Source URL: www.cs.toronto.edu

Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling Andrew Kae∗1 , Kihyuk Sohn∗2 , Honglak Lee2 , Erik Learned-Miller1 1 University of Massachusetts, Amherst, MA, USA, {akae,elm}@cs.umass.edu 2 Uni

Source URL: web.eecs.umich.edu

Charlie Tang Department of Computer Science, University of Toronto, Canada Gated Boltzmann Machine for Recognition under Occlusion

Source URL: www.cs.toronto.edu

Visually Debugging Restricted Boltzmann Machine Training with a 3D Example Jason Yosinski Hod Lipson Department of Computer Science, Cornell University, Ithaca, NY, USA

Source URL: yosinski.com