25 citations · 25 across the 4 of their papers we have counts for
4 papers
Turbulent pair dispersion with Stochastic Generative Diffusion Models
Andrei Pantea, Luca Biferale, Michele Buzzicotti +3
Recent advances in data-driven modeling have shown that diffusion models can successfully generate synthetic Lagrangian trajectories in turbulent flows. Building on this progress,…
PRIVET: PRoximIty leakage detection Via Extreme value Theory
Antoine Szatkownik, Aurélien Decelle, Beatriz Seoane +7
Deep generative models are often trained on sensitive data, such as genetic sequences, health data, or more broadly, any copyrighted, licensed or protected content. This raises cri…
Multi-Level GNN Preconditioner for Solving Large Scale Problems
Matthieu Nastorg, Jean-Marc Gratien, Thibault Faney +3
Large-scale numerical simulations often come at the expense of daunting computations. High-Performance Computing has enhanced the process, but adapting legacy codes to leverage par…
Training recurrent networks online without backtracking
Yann Ollivier, Corentin Tallec, Guillaume Charpiat
We introduce the "NoBackTrack" algorithm to train the parameters of dynamical systems such as recurrent neural networks. This algorithm works in an online, memoryless setting, thus…