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Linear Complexity Self-Attention With 3rd Order Polynomials

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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

Linear Complexity Self-Attention With 3rd Order Polynomials

Graph Chatbot

Chattez avec Graph Search

Random matrix methods for high-dimensional machine learning models

Intraday solar irradiance forecasting using public cameras

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Aggregating Spatial and Photometric Context for Photometric Stereo

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Topics in statistical physics of high-dimensional machine learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Random matrix methods for high-dimensional machine learning models

Intraday solar irradiance forecasting using public cameras

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Aggregating Spatial and Photometric Context for Photometric Stereo

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Topics in statistical physics of high-dimensional machine learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination