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3D Structure From 2D Microscopy Images Using Deep Learning

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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

3D Structure From 2D Microscopy Images Using Deep Learning

Graph Chatbot

Chattez avec Graph Search

Topics in statistical physics of high-dimensional machine learning

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

Live-cell imaging powered by computation

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Aggregating Spatial and Photometric Context for Photometric Stereo

Structure-function analysis of the cyclic β-1,2-glucan synthase from Agrobacterium tumefaciens

Robust NAS under adversarial training: benchmark, theory, and beyond

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

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Topics in statistical physics of high-dimensional machine learning

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

Live-cell imaging powered by computation

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Aggregating Spatial and Photometric Context for Photometric Stereo

Structure-function analysis of the cyclic β-1,2-glucan synthase from Agrobacterium tumefaciens

Robust NAS under adversarial training: benchmark, theory, and beyond

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

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning