Pages that link to "Item:Q3503734"

The following pages link to Representational Power of Restricted Boltzmann Machines and Deep Belief Networks (Q3503734):

Displaying 50 items.

• A topological insight into restricted Boltzmann machines (Q331673) (← links)
• An implicitization challenge for binary factor analysis (Q607054) (← links)
• The shape Boltzmann machine: a strong model of object shape (Q740413) (← links)
• Two-layer contractive encodings for learning stable nonlinear features (Q890731) (← links)
• Deep learning of support vector machines with class probability output networks (Q890735) (← links)
• Training restricted Boltzmann machines: an introduction (Q898295) (← links)
• Deep Boltzmann machines: rigorous results at arbitrary depth (Q2042343) (← links)
• Necessary and sufficient conditions of proper estimators based on self density ratio for unnormalized statistical models (Q2179310) (← links)
• On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-bipolar restricted Boltzmann machines (Q2181099) (← links)
• A new mechanical approach to handle generalized Hopfield neural networks (Q2182875) (← links)
• An adaptive deep Q-learning strategy for handwritten digit recognition (Q2182881) (← links)
• Accelerating deep learning with memcomputing (Q2182923) (← links)
• Storing, learning and retrieving biased patterns (Q2247160) (← links)
• Discriminative deep belief networks for visual data classification (Q2275979) (← links)
• Class sparsity signature based restricted Boltzmann machine (Q2289620) (← links)
• Functional clones and expressibility of partition functions (Q2357376) (← links)
• Hierarchical models as marginals of hierarchical models (Q2411283) (← links)
• Dynamical analysis of contrastive divergence learning: restricted Boltzmann machines with Gaussian visible units (Q2418189) (← links)
• Explicit demonstration of initial state construction in artificial neural networks using netket and IBM Q experience platform (Q2677565) (← links)
• \(p\)-adic statistical field theory and deep belief networks (Q2685103) (← links)
• Universal approximation results for the temporal restricted Boltzmann machine and the recurrent temporal restricted Boltzmann machine (Q2834488) (← links)
• Augmentable gamma belief networks (Q2834494) (← links)
• Exploring strategies for training deep neural networks (Q2880870) (← links)
• An efficient learning procedure for deep Boltzmann machines (Q2919431) (← links)
• Design and application of continuous deep belief network (Q2992002) (← links)
• Refinements of Universal Approximation Results for Deep Belief Networks and Restricted Boltzmann Machines (Q3015455) (← links)
• Deep belief network based on noisy data and clean data (Q3306913) (← links)
• Modeling the Correlated Activity of Neural Populations: A Review (Q3379586) (← links)
• Restricted Boltzmann machines (Q3461098) (← links)
• Deep, Narrow Sigmoid Belief Networks Are Universal Approximators (Q3536226) (← links)
• Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines (Q3568370) (← links)
• Deep Belief Networks Are Compact Universal Approximators (Q3583502) (← links)
• (Q4558488) (← links)
• GSNs: generative stochastic networks (Q4603726) (← links)
• Neural network operations and Susuki–Trotter evolution of neural network states (Q4620299) (← links)
• The DBM-ELM deep network model (Q4640777) (← links)
• Unifying neural-network quantum states and correlator product states via tensor networks (Q4644127) (← links)
• Review and prospect on deep belief network (Q4998048) (← links)
• (Q4999034) (← links)
• Free energies of Boltzmann machines: self-averaging, annealed and replica symmetric approximations in the thermodynamic limit (Q5006959) (← links)
• Equilibrium and non-equilibrium regimes in the learning of restricted Boltzmann machines* (Q5055423) (← links)
• Minimal model of permutation symmetry in unsupervised learning (Q5059115) (← links)
• ‘Place-cell’ emergence and learning of invariant data with restricted Boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space (Q5061428) (← links)
• Features Reweighting and Selection in ligand-based Virtual Screening for Molecular Similarity Searching Based on Deep Belief Networks (Q5066679) (← links)
• Decreasing the Size of the Restricted Boltzmann Machine (Q5154145) (← links)
• Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks (Q5162362) (← links)
• When Does a Mixture of Products Contain a Product of Mixtures? (Q5251565) (← links)
• Enhanced Gradient for Training Restricted Boltzmann Machines (Q5327190) (← links)
• Dimension of Marginals of Kronecker Product Models (Q5347296) (← links)
• An Infinite Restricted Boltzmann Machine (Q5380542) (← links)