activity
20092024
most citedWasserstein Discriminant Analysis

91 citations · 395 across the 40 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.LG2023

Adversarial Sample Detection Through Neural Network Transport Dynamics

Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy

We propose a detector of adversarial samples that is based on the view of neural networks as discrete dynamic systems. The detector tells clean inputs from abnormal ones by compari…

cs.LG2023★ 1 cited

Unifying GANs and Score-Based Diffusion as Generative Particle Models

Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos +4

Particle-based deep generative models, such as gradient flows and score-based diffusion models, have recently gained traction thanks to their striking performance. Their principle…

cs.LG2023★ 1 cited

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals

Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy +4

When dealing with electro or magnetoencephalography records, many supervised prediction tasks are solved by working with covariance matrices to summarize the signals. Learning with…

cs.LG2023

Approximating DTW with a convolutional neural network on EEG data

Hugo Lerogeron, Romain Picot-Clemente, Alain Rakotomamonjy +1

Dynamic Time Wrapping (DTW) is a widely used algorithm for measuring similarities between two time series. It is especially valuable in a wide variety of applications, such as clus…

cs.LG2023★ 6 cited

Personalised Federated Learning On Heterogeneous Feature Spaces

Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz +1

Most personalised federated learning (FL) approaches assume that raw data of all clients are defined in a common subspace i.e. all clients store their data according to the same sc…