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Lupulus: A Flexible Hardware Accelerator For Neural Networks

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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

Lupulus: A Flexible Hardware Accelerator For Neural Networks

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Chattez avec Graph Search

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Modified capillary number to standardize droplet generation in suction-driven microfluidics

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Partial discharge localization in power transformer tanks using machine learning methods

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

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

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Modified capillary number to standardize droplet generation in suction-driven microfluidics

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Partial discharge localization in power transformer tanks using machine learning methods

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

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