Pages that link to "Item:Q3101410"
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The following pages link to Reducing the Dimensionality of Data with Neural Networks (Q3101410):
Displaying 50 items.
- Convolutional autoencoder and conditional random fields hybrid for predicting spatial-temporal chaos (Q5213524) (← links)
- Deep learning the holographic black hole with charge (Q5221253) (← links)
- DNN-PPI: A LARGE-SCALE PREDICTION OF PROTEIN–PROTEIN INTERACTIONS BASED ON DEEP NEURAL NETWORKS (Q5230429) (← links)
- SwitchNet: A Neural Network Model for Forward and Inverse Scattering Problems (Q5240806) (← links)
- Multilevel Artificial Neural Network Training for Spatially Correlated Learning (Q5241254) (← links)
- Nonlinear mode decomposition with convolutional neural networks for fluid dynamics (Q5243565) (← links)
- Adaptive bridge control strategy for opinion evolution on social networks (Q5264557) (← links)
- A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets (Q5266391) (← links)
- Justifying and Generalizing Contrastive Divergence (Q5323837) (← links)
- Learning the Dynamics of Objects by Optimal Functional Interpolation (Q5327151) (← links)
- Enhanced Gradient for Training Restricted Boltzmann Machines (Q5327190) (← links)
- Large Margin Low Rank Tensor Analysis (Q5378344) (← links)
- Deep Learning with Dynamic Spiking Neurons and Fixed Feedback Weights (Q5380664) (← links)
- Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (Q5382481) (← links)
- Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning (Q5440970) (← links)
- Bucket renormalization for approximate inference (Q5854127) (← links)
- Learning Individualized Treatment Rules for Multiple-Domain Latent Outcomes (Q5857109) (← links)
- Dynamical Variational Autoencoders: A Comprehensive Review (Q5863990) (← links)
- Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations (Q5864754) (← links)
- Gaussian-spherical restricted Boltzmann machines (Q5869954) (← links)
- DeepSym: Deep Symbol Generation and Rule Learning for Planning from Unsupervised Robot Interaction (Q5870493) (← links)
- Research on three-step accelerated gradient algorithm in deep learning (Q5880102) (← links)
- Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder (Q5886859) (← links)
- Approximate and discrete Euclidean vector bundles (Q5887140) (← links)
- A converged deep graph semi-NMF algorithm for learning data representation (Q6042581) (← links)
- Koopman analysis of nonlinear systems with a neural network representation (Q6043737) (← links)
- Thermodynamics of bidirectional associative memories (Q6046084) (← links)
- Representations of hypergraph states with neural networks* (Q6046360) (← links)
- LSTM-based approach for predicting periodic motions of an impacting system via transient dynamics (Q6054556) (← links)
- A distributed optimisation framework combining natural gradient with Hessian-free for discriminative sequence training (Q6055115) (← links)
- Transfer-RLS method and transfer-FORCE learning for simple and fast training of reservoir computing models (Q6055117) (← links)
- Epicasting: an ensemble wavelet neural network for forecasting epidemics (Q6057959) (← links)
- Nonlinear reduced-order modeling for three-dimensional turbulent flow by large-scale machine learning (Q6060754) (← links)
- Estimating propensity scores using neural networks and traditional methods: a comparative simulation study (Q6061348) (← links)
- Probabilistic partition of unity networks for high‐dimensional regression problems (Q6062830) (← links)
- Statistical Inference, Learning and Models in Big Data (Q6064668) (← links)
- Discriminative group-sparsity constrained broad learning system for visual recognition (Q6066149) (← links)
- Predicting turbulent dynamics with the convolutional autoencoder echo state network (Q6067855) (← links)
- Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution (Q6068233) (← links)
- The emergence of a concept in shallow neural networks (Q6072447) (← links)
- Surrogate modeling for high dimensional uncertainty propagation via deep kernel polynomial chaos expansion (Q6072820) (← links)
- Successfully and efficiently training deep multi-layer perceptrons with logistic activation function simply requires initializing the weights with an appropriate negative mean (Q6077039) (← links)
- Multibody dynamics and control using machine learning (Q6078031) (← links)
- Fast convergence rates of deep neural networks for classification (Q6078714) (← links)
- Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow (Q6080313) (← links)
- Deep multimodal autoencoder for crack criticality assessment (Q6089256) (← links)
- Predicting circRNA-disease associations based on autoencoder and graph embedding (Q6092067) (← links)
- Non‐intrusive reduced‐order modeling using convolutional autoencoders (Q6092270) (← links)
- Physics-informed data-driven model for fluid flow in porous media (Q6093463) (← links)
- A taxonomy for similarity metrics between Markov decision processes (Q6097106) (← links)
