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Event-driven acquisition for content-enriched microscopy

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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

Event-driven acquisition for content-enriched microscopy

Graph Chatbot

Chattez avec Graph Search

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

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

Sparse autoregressive neural networks for classical spin systems

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

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Machine Learning for Modeling Stock Returns

Optimizing Dynamic Aperture Studies with Active Learning

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

Enabling Uncertainty Estimation in Iterative Neural Networks

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

Sparse autoregressive neural networks for classical spin systems

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

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Optimizing Dynamic Aperture Studies with Active Learning

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

Enabling Uncertainty Estimation in Iterative Neural Networks

Machine Learning for Modeling Stock Returns

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