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Reconstruction Methods for Cryo-Electron Microscopy: From Model-based to Data-driven

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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

Reconstruction Methods for Cryo-Electron Microscopy: From Model-based to Data-driven

Graph Chatbot

Chattez avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Topics in statistical physics of high-dimensional machine learning

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

Structural study of nickelate based heterostructures

Machine Learning for Modeling Stock Returns

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

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

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Topics in statistical physics of high-dimensional machine learning

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

Structural study of nickelate based heterostructures

Machine Learning for Modeling Stock Returns

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

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

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts