Robust Stochastically-Descending Unrolled Networks

2 code implementations • 25 Dec 2023 • Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro

To tackle these problems, we provide deep unrolled architectures with a stochastic descent nature by imposing descending constraints during training.

Image Inpainting

Stochastic Unrolled Federated Learning

1 code implementation • 24 May 2023 • Samar Hadou, Navid Naderializadeh, Alejandro Ribeiro

We introduce Stochastic UnRolled Federated learning (SURF), a method that expands algorithm unrolling to federated learning in order to expedite its convergence.

Federated Learning Rolling Shutter Correction

Space-Time Graph Neural Networks with Stochastic Graph Perturbations

no code implementations • 28 Oct 2022 • Samar Hadou, Charilaos Kanatsoulis, Alejandro Ribeiro

Space-time graph neural networks (ST-GNNs) are recently developed architectures that learn efficient graph representations of time-varying data.

Transfer Learning

Space-Time Graph Neural Networks

no code implementations • ICLR 2022 • Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro

We introduce a generic definition of convolution operators that mimic the diffusion process of signals over its underlying support.