output
20202022
most citedExpressive Power of Invariant and Equivariant Graph Neural Networks

22 citations

9 papers

cs.LG2022★ 1 cited

On Non-Linear operators for Geometric Deep Learning

Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna +1

This work studies operators mapping vector and scalar fields defined over a manifold , and which commute with its group of diffeomorphisms .…

cs.CR2022★ 1 cited

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging

Edwige Cyffers, Mathieu Even, Aurélien Bellet +1

Decentralized optimization is increasingly popular in machine learning for its scalability and efficiency. Intuitively, it should also provide better privacy guarantees, as nodes o…

eess.SP2022

Analysis of a Spatially Correlated Vehicular Network Assisted by Cox-distributed Vehicle Relays

Chang-Sik Choi, François Baccelli

In vehicle-to-all (V2X) communications, roadside units (RSUs) play an essential role in connecting various network devices. In some cases, users may not be well-served by RSUs due…

math.PR2022★ 1 cited

Coupling from the Past for the Null Recurrent Markov Chain

François Baccelli, Mir-Omid Haji-Mirsadeghi, Sayeh Khaniha

The Doeblin Graph of a countable state space Markov chain describes the joint pathwise evolutions of the Markov dynamics starting from all possible initial conditions, with two pat…

cs.NI2021★ 1 cited

Online Stochastic Matching: A Polytope Perspective

C{é}line Comte, Fabien Mathieu, Sushil Mahavir Varma +1

Stochastic dynamic matching problems have recently gained attention in the stochastic-modeling community due to their diverse applications, such as supply-chain management and kidn…

stat.ML2020★ 1 cited

Particle gradient descent model for point process generation

Antoine Brochard, Bartłomiej Błaszczyszyn, Stéphane Mallat +1

This paper presents a statistical model for stationary ergodic point processes, estimated from a single realization observed in a square window. With existing approaches in stochas…