Publications associées à Theory of Deep Learning: Neural Tangent Kernel and Beyond

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Network Simplification: the Gaussian N-Relay Diamond Network

Christina Fragouli, Ayfer Özgür Aydin

We consider the Gaussian

N

-relay diamond network, where a source wants to communicate to a destination through a layer of

N

-relay nodes. We investigate the following question: What fraction of the capacity can we maintain by using only

k

out of the $ ...

2010

Theory of Deep Learning: Neural Tangent Kernel and Beyond

Graph Chatbot

Chattez avec Graph Search

Data Synthesization for Classification in Autonomous Robotic Grasping System Using ‘Catalogue’-Style Images

The Robustness of Deep Networks - A geometric perspective

A Formally Verified NAT

Neural conditional random fields

Network Simplification: the Gaussian N-Relay Diamond Network

Regularization Networks for Inverse Problems: A state-space approach

Improving Face Authetication Using Virtual Samples

Improving Face Authetication Using Virtual Samples

Regularization Networks for Inverse Problems: A state-space approach

Consistent identification of NARX models via regularization networks

Neural conditional random fields

Network Simplification: the Gaussian N-Relay Diamond Network

The Robustness of Deep Networks - A geometric perspective

Regularization Networks for Inverse Problems: A state-space approach

A Formally Verified NAT

Consistent identification of NARX models via regularization networks

Regularization Networks for Inverse Problems: A state-space approach

Improving Face Authetication Using Virtual Samples

Improving Face Authetication Using Virtual Samples

Data Synthesization for Classification in Autonomous Robotic Grasping System Using ‘Catalogue’-Style Images