Pages that link to "Item:Q2880870"
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The following pages link to Exploring strategies for training deep neural networks (Q2880870):
Displaying 14 items.
- Non-iterative and fast deep learning: multilayer extreme learning machines (Q2005317) (← links)
- FCM-DNN: diagnosing coronary artery disease by deep accuracy fuzzy C-means clustering model (Q2130428) (← links)
- Deep learning solver for solving advection-diffusion equation in comparison to finite difference methods (Q2170855) (← links)
- Block layer decomposition schemes for training deep neural networks (Q2173515) (← links)
- An adaptive deep Q-learning strategy for handwritten digit recognition (Q2182881) (← links)
- Landscape and training regimes in deep learning (Q2231925) (← links)
- Deep autoencoders for physics-constrained data-driven nonlinear materials modeling (Q2237774) (← links)
- Why does unsupervised pre-training help deep learning? (Q2896045) (← links)
- (Q4999020) (← links)
- A Fast Learning Algorithm for Deep Belief Nets (Q5476682) (← links)
- Discrete-time nonlinear feedback linearization via physics-informed machine learning (Q6078485) (← links)
- Evolutionary multi-objective design of autoencoders for compact representation of histopathology whole slide images (Q6551082) (← links)
- Statistical theory for image classification using deep convolutional neural network with cross-entropy loss under the hierarchical max-pooling model (Q6616182) (← links)
- Construction of grid operators for multilevel solvers: a neural network approach (Q6630159) (← links)
