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Highway network

Publications associées (52)

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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

Highway network

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Efficient and Accurate Peer-to-Peer Training of Machine Learning Based Home Thermal Models

Universal Approximation Property of Hamiltonian Deep Neural Networks

Bayesian reconstruction of memories stored in neural networks from their connectivity

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems

Generalization Properties of NAS under Activation and Skip Connection Search

Global information processing in feedforward deep networks

Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach

Population receptive fields isolate or combine target and flankers in (un)crowding

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Efficient and Accurate Peer-to-Peer Training of Machine Learning Based Home Thermal Models

Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach

Population receptive fields isolate or combine target and flankers in (un)crowding

Universal Approximation Property of Hamiltonian Deep Neural Networks

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Global information processing in feedforward deep networks

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems

Generalization Properties of NAS under Activation and Skip Connection Search

Bayesian reconstruction of memories stored in neural networks from their connectivity