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Reservoir optimization in recurrent neural networks using properties of Kronecker product

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Reservoir optimization in recurrent neural networks using properties of Kronecker product

Graph Chatbot

Chattez avec Graph Search

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Deep Learning Generalization with Limited and Noisy Labels

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Transformer Models for Vision

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

An exact mapping from ReLU networks to spiking neural networks

Probabilistic methods for neural combinatorial optimization

Time Series Analysis of Urban Liveability

Learned Compressive Representations for Single-Photon 3D Imaging

Deep Learning Generalization with Limited and Noisy Labels

Time Series Analysis of Urban Liveability

Transformer Models for Vision

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Probabilistic methods for neural combinatorial optimization

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Learned Compressive Representations for Single-Photon 3D Imaging

An exact mapping from ReLU networks to spiking neural networks