Publications associées à Neuronal Dynamics - Computational Neuroscience of Single Neurons

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Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

In this work, we investigate the effect of momentum on the optimisation trajectory of gradient descent. We leverage a continuous-time approach in the analysis of momentum gradient descent with step size

\gamma

and momentum parameter

\beta

that allows u ...

2024

Neuronal Dynamics - Computational Neuroscience of Single Neurons

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Predicting the long-term collective behaviour of fish pairs with deep learning

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Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex

Membrane specificity of the human cholesterol transfer protein STARD4

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Spectral Estimators for High-Dimensional Matrix Inference

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Predicting the long-term collective behaviour of fish pairs with deep learning

Spectral Estimators for High-Dimensional Matrix Inference

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

Robot Learning using Tensor Networks

Membrane specificity of the human cholesterol transfer protein STARD4

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex

Partial discharge localization in power transformer tanks using machine learning methods

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks