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Time Series Analysis of Urban Liveability

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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

Time Series Analysis of Urban Liveability

Graph Chatbot

Chattez avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Deep Learning Generalization with Limited and Noisy Labels

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Transformer Models for Vision

Polynomial-time universality and limitations of deep learning

Bed Topography Inference from Velocity Field Using Deep Learning.

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Explicit representations for Banach subspaces of Lizorkin distributions

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Bed Topography Inference from Velocity Field Using Deep Learning.

Deep Learning Generalization with Limited and Noisy Labels

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

Transformer Models for Vision

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Polynomial-time universality and limitations of deep learning

Explicit representations for Banach subspaces of Lizorkin distributions