activity
20202026
most citedFault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

43 citations · 74 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2026

The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems

Enrico Angelelli, Andrea Mor, Carlotta Orsenigo +2

In this paper, machine learning techniques are used to forecast the difference between bike returns and withdrawals at each station of a bike sharing system. The forecasts are inte…

cs.LG2024★ 1 cited

Evaluating deep learning models for fault diagnosis of a rotating machinery with epistemic and aleatoric uncertainty

Reza Jalayer, Masoud Jalayer, Andrea Mor +2

Uncertainty-aware deep learning (DL) models recently gained attention in fault diagnosis as a way to promote the reliable detection of faults when out-of-distribution (OOD) data ar…

cs.LG2022★ 43 cited

Fault Detection and Diagnosis with Imbalanced and Noisy Data: A Hybrid Framework for Rotating Machinery

Masoud Jalayer, Amin Kaboli, Carlotta Orsenigo +1

Fault diagnosis plays an essential role in reducing the maintenance costs of rotating machinery manufacturing systems. In many real applications of fault detection and diagnosis, d…

cs.CV2021

Automatic Visual Inspection of Rare Defects: A Framework based on GP-WGAN and Enhanced Faster R-CNN

Masoud Jalayer, Reza Jalayer, Amin Kaboli +2

A current trend in industries such as semiconductors and foundry is to shift their visual inspection processes to Automatic Visual Inspection (AVI) systems, to reduce their costs,…

cs.CL2021★ 18 cited

ELECTRAMed: a new pre-trained language representation model for biomedical NLP

Giacomo Miolo, Giulio Mantoan, Carlotta Orsenigo

The overwhelming amount of biomedical scientific texts calls for the development of effective language models able to tackle a wide range of biomedical natural language processing…

physics.soc-ph2020★ 12 cited

CoV-ABM: A stochastic discrete-event agent-based framework to simulate spatiotemporal dynamics of COVID-19

Masoud Jalayer, Carlotta Orsenigo, Carlo Vercellis

The paper develops a stochastic Agent-Based Model (ABM) mimicking the spread of infectious diseases in geographical domains. The model is designed to simulate the spatiotemporal sp…