22 citations · 43 across the 9 of their papers we have counts for
5 papers · 1 filter
Regularization properties of adversarially-trained linear regression
Antônio H. Ribeiro, Dave Zachariah, Francis Bach +1
State-of-the-art machine learning models can be vulnerable to very small input perturbations that are adversarially constructed. Adversarial training is an effective approach to de…
End-to-end Risk Prediction of Atrial Fibrillation from the 12-Lead ECG by Deep Neural Networks
Theogene Habineza, Antônio H. Ribeiro, Daniel Gedon +3
Background: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of…
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao +2
This work aims to improve the applicability of diffusion models in realistic image restoration. Specifically, we enhance the diffusion model in several aspects such as network arch…
On the trade-off between event-based and periodic state estimation under bandwidth constraints
Dominik Baumann, Thomas B. Schön
Event-based methods carefully select when to transmit information to enable high-performance control and estimation over resource-constrained communication networks. However, they…
Deep networks for system identification: a Survey
Gianluigi Pillonetto, Aleksandr Aravkin, Daniel Gedon +3
Deep learning is a topic of considerable current interest. The availability of massive data collections and powerful software resources has led to an impressive amount of results i…