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Distributed Learning of CNNs on Heterogeneous CPU/GPU Architectures

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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

Distributed Learning of CNNs on Heterogeneous CPU/GPU Architectures

Graph Chatbot

Chattez avec Graph Search

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

EdgeAI-Aware Design of In-Memory Computing Architectures

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Random matrix methods for high-dimensional machine learning models

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Topics in statistical physics of high-dimensional machine learning

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

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

EdgeAI-Aware Design of In-Memory Computing Architectures

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Random matrix methods for high-dimensional machine learning models

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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

Topics in statistical physics of high-dimensional machine learning