most citedVARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Integrating SystemC TLM into FMI 3.0 Co-Simulations with an Open-Source Approach

Andrei Mihai Albu, Giovanni Pollo, Alessio Burrello +6

The growing complexity of cyber-physical systems, particularly in automotive applications, has increased the demand for efficient modeling and cross-domain co-simulation techniques…

cs.CL2025

Automatic integration of SystemC in the FMI standard for Software-defined Vehicle design

Giovanni Pollo, Andrei Mihai Albu, Alessio Burrello +6

The recent advancements of the automotive sector demand robust co-simulation methodologies that enable early validation and seamless integration across hardware and software domain…

cs.RO2025

MEbots: Integrating a RISC-V Virtual Platform with a Robotic Simulator for Energy-aware Design

Giovanni Pollo, Mohamed Amine Hamdi, Matteo Risso +9

Virtual Platforms (VPs) enable early software validation of autonomous systems' electronics, reducing costs and time-to-market. While many VPs support both functional and non-funct…

cs.LG20241 cited

Coupling Neural Networks and Physics Equations For Li-Ion Battery State-of-Charge Prediction

Giovanni Pollo, Alessio Burrello, Enrico Macii +3

Estimating the evolution of the battery's State of Charge (SoC) in response to its usage is critical for implementing effective power management policies and for ultimately improvi…

cs.LG20243 cited

VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge

Alessio Mascolini, Sebastiano Gaiardelli, Francesco Ponzio +5

Detecting complex anomalies on massive amounts of data is a crucial task in Industry 4.0, best addressed by deep learning. However, available solutions are computationally demandin…