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Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

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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

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Graph Chatbot

Chattez avec Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

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

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

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

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

Semantic Shape Editing with Parametric Implicit Templates

Enabling Uncertainty Estimation in Iterative Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Semantic Shape Editing with Parametric Implicit Templates

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

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

Enabling Uncertainty Estimation in Iterative Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Aggregating Spatial and Photometric Context for Photometric Stereo

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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