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Metric learning for kernel ridge regression: assessment of molecular similarity

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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

Metric learning for kernel ridge regression: assessment of molecular similarity

Graph Chatbot

Chattez avec Graph Search

Efficient and insightful descriptors for representing molecular and material space

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

Residual-based attention in physics-informed neural networks

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Partial discharge localization in power transformer tanks using machine learning methods

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Efficient and insightful descriptors for representing molecular and material space

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Partial discharge localization in power transformer tanks using machine learning methods

Residual-based attention in physics-informed neural networks