Nature

Shrinkage Estimation and Balanced Loss Functions in Multivariate Normal Distribution

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
IEEE

Fusion Graph Structure Learning-Based Multivariate Time Series Anomaly Detection With Structured Prior Knowledge

Abstract: Multivariate time series anomaly detection (MTSAD) plays a crucial role in the Internet of Things (IoT) to identify device malfunction or system attacks. Graph neural networks (GNN) are ...
IEEE

Graph-Dictionary Signal Model for Sparse Representation of Multivariate Data

Abstract: Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational ...
University of Geneva

David Cimasoni

Gaetan Simian: PhD student (co-direction with Anthony Conway ), started February 2023. Miguel Orbegozo Rodriguez: postdoc, started September 2025. Livio Ferretti: postdoc, September 2023-February 2025 ...
GitHub

Spatio-temporal Fusion Flow with Dynamic Graph Leaning for Unsupervised Multivariate Time Series Anomaly Detection

Detecting anomalies in multivariate time series (MTS) is essential for maintaining system safety in industrial environments. Due to the challenges associated with acquiring labeled data, unsupervised ...
Frontiers

A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low ...

Purpose: This study aimed to develop a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NAC) in patients with Human Epidermal Growth Factor Receptor 2 (HER2)-low breast cancer, ...