Pierre Marion | DeepAI

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∙ 09/03/2023

Implicit regularization of deep residual networks towards neural ODEs

Residual neural networks are state-of-the-art deep learning models. Thei...

0 Pierre Marion, et al. ∙

∙ 05/11/2023

Generalization bounds for neural ordinary differential equations and deep residual networks

Neural ordinary differential equations (neural ODEs) are a popular famil...

0 Pierre Marion, et al. ∙

∙ 04/19/2023

Leveraging the two timescale regime to demonstrate convergence of neural networks

We study the training dynamics of shallow neural networks, in a two-time...

0 Pierre Marion, et al. ∙

∙ 06/14/2022

Scaling ResNets in the Large-depth Regime

Deep ResNets are recognized for achieving state-of-the-art results in co...

0 Pierre Marion, et al. ∙

∙ 09/01/2021

Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs

We tackle the problem of weakly-supervised conversational Question Answe...

0 Pierre Marion, et al. ∙

∙ 06/02/2021

Framing RNN as a kernel method: A neural ODE approach

Building on the interpretation of a recurrent neural network (RNN) as a ...

0 Adeline Fermanian, et al. ∙

∙ 12/18/2020

A Tool for Custom Construction of QMC and RQMC Point Sets

We present LatNet Builder, a software tool to find good parameters for l...

0 Pierre L'Ecuyer, et al. ∙

∙ 10/05/2019

An algorithm to compute the t-value of a digital net and of its projections

Digital nets are among the most successful methods to construct low-disc...

0 Pierre Marion, et al. ∙

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