Pages that link to "Item:Q4992247"
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The following pages link to On Random Matrices Arising in Deep Neural Networks. Gaussian Case (Q4992247):
Displaying 11 items.
- A random matrix approach to neural networks (Q1650102) (← links)
- Products of many large random matrices and gradients in deep neural networks (Q2181980) (← links)
- Asymptotic freeness of layerwise Jacobians caused by invariance of multilayer perceptron: the Haar orthogonal case (Q2699717) (← links)
- A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent* (Q5020045) (← links)
- Corrections to “Deep Neural Networks With Random Gaussian Weights: A Universal Classification Strategy?” [Jul 1, 2016 3444-3457] (Q5102591) (← links)
- (Q5159443) (← links)
- Universal characteristics of deep neural network loss surfaces from random matrix theory (Q5878969) (← links)
- Eigenvalue distribution of large random matrices arising in deep neural networks: Orthogonal case (Q5883551) (← links)
- Large-dimensional random matrix theory and its applications in deep learning and wireless communications (Q6063730) (← links)
- The Law of Multiplication of Large Random Matrices Revisited (Q6151696) (← links)
- On random matrices arising in deep neural networks: General I.I.D. case (Q6163573) (← links)
