Publications associées à Theory of representation learning in cortical neural networks

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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

Theory of representation learning in cortical neural networks

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The neural correlates of topographical disorientation-a lesion analysis study

Meta-learning to address diverse Earth observation problems across resolutions

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Butterfly effects in perceptual development: A review of the 'adaptive initial degradation' hypothesis

Revisiting Character-level Adversarial Attacks for Language Models

Machine Learning Security Against Data Poisoning: Are We There Yet?

Deep Learning Generalization with Limited and Noisy Labels

Supervised learning and inference of spiking neural networks with temporal coding

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Probabilistic methods for neural combinatorial optimization

Supervised learning and inference of spiking neural networks with temporal coding

Butterfly effects in perceptual development: A review of the 'adaptive initial degradation' hypothesis

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Deep Learning Generalization with Limited and Noisy Labels

The neural correlates of topographical disorientation-a lesion analysis study

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Revisiting Character-level Adversarial Attacks for Language Models

Machine Learning Security Against Data Poisoning: Are We There Yet?

Probabilistic methods for neural combinatorial optimization

Meta-learning to address diverse Earth observation problems across resolutions