Pages that link to "Item:Q5476682"
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The following pages link to A Fast Learning Algorithm for Deep Belief Nets (Q5476682):
Displaying 50 items.
- Deep learned finite elements (Q2021024) (← links)
- Multidisciplinary pattern recognition applications: a review (Q2026301) (← links)
- Deep autoencoder based energy method for the bending, vibration, and buckling analysis of Kirchhoff plates with transfer learning (Q2035195) (← links)
- A theory of incremental compression (Q2056272) (← links)
- Theory of deep convolutional neural networks. II: Spherical analysis (Q2057723) (← links)
- Deep learning on image denoising: an overview (Q2057732) (← links)
- A comprehensive survey and analysis of generative models in machine learning (Q2065961) (← links)
- Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate (Q2096832) (← links)
- A capsule-unified framework of deep neural networks for graphical programming (Q2099868) (← links)
- An iterative stacked weighted auto-encoder (Q2099909) (← links)
- Mathematical analysis of finite parameter deep neural network models with skip connections from the viewpoint of representation sets (Q2107473) (← links)
- Approximation of functions from korobov spaces by deep convolutional neural networks (Q2108977) (← links)
- The elementary excitation of spin lattice models: the quasiparticles of Gentile statistics (Q2128747) (← links)
- On an artificial neural network for inverse scattering problems (Q2134547) (← links)
- Parameter inference in a probabilistic model from data: regulation of transition rate in the Monte Carlo method (Q2148699) (← links)
- Hybrid deep learning model-based prediction of images related to cyberbullying (Q2162145) (← links)
- Designing phononic crystal with anticipated band gap through a deep learning based data-driven method (Q2176922) (← links)
- Deep neural networks for texture classification -- a theoretical analysis (Q2179105) (← links)
- Towards understanding sparse filtering: a theoretical perspective (Q2179299) (← links)
- Necessary and sufficient conditions of proper estimators based on self density ratio for unnormalized statistical models (Q2179310) (← links)
- Probabilistic lower bounds for approximation by shallow perceptron networks (Q2181058) (← links)
- A deep belief network with PLSR for nonlinear system modeling (Q2181070) (← links)
- Synchronization of hybrid coupled reaction-diffusion neural networks with time delays via generalized intermittent control with spacial sampled-data (Q2181078) (← links)
- An adaptive deep Q-learning strategy for handwritten digit recognition (Q2182881) (← links)
- Accelerating deep learning with memcomputing (Q2182923) (← links)
- Theory of deep convolutional neural networks: downsampling (Q2185717) (← links)
- Preserving differential privacy in deep neural networks with relevance-based adaptive noise imposition (Q2185767) (← links)
- Data science applications to string theory (Q2187812) (← links)
- An unsupervised parameter learning model for RVFL neural network (Q2188218) (← links)
- Latent structure preserving hashing (Q2193760) (← links)
- Deep multimodal fusion: a hybrid approach (Q2193912) (← links)
- An unsupervised fault diagnosis method for rolling bearing using STFT and generative neural networks (Q2198631) (← links)
- Impact of random weights on nonlinear system identification using convolutional neural networks (Q2201655) (← links)
- Sim2vec: node similarity preserving network embedding (Q2215048) (← links)
- Nonequilibrium thermodynamics of self-supervised learning (Q2236536) (← links)
- TONR: an exploration for a novel way combining neural network with topology optimization (Q2246269) (← links)
- Rejoinder of: Treelets -- an adaptive multi-scale basis for spare unordered data (Q2271332) (← links)
- SO(8) supergravity and the magic of machine learning (Q2273413) (← links)
- Discriminative deep belief networks for visual data classification (Q2275979) (← links)
- Class sparsity signature based restricted Boltzmann machine (Q2289620) (← links)
- Nonredundant sparse feature extraction using autoencoders with receptive fields clustering (Q2292197) (← links)
- Deep neural mapping support vector machines (Q2292203) (← links)
- Limitations of shallow nets approximation (Q2292226) (← links)
- Fast structure learning for deep feedforward networks via tree skeleton expansion (Q2297774) (← links)
- Universality of deep convolutional neural networks (Q2300759) (← links)
- On the relative expressiveness of Bayesian and neural networks (Q2302782) (← links)
- A DBN-based deep neural network model with multitask learning for online air quality prediction (Q2303386) (← links)
- Sum-product graphical models (Q2303664) (← links)
- A survey on semi-supervised learning (Q2303675) (← links)
- A surface-to-surface contact search method enhanced by deep learning (Q2308818) (← links)
