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20242026
most citedIndustrial Machines Health Prognosis using a Transformer-based Framework

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Quantile-Led Feature Extraction for Multi-Horizon Predictive Maintenance in Industrial Manufacturing Systems

David J Poland, Daniele Ravi, Na Helian

In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused while the downstream model or…

cs.AI2026

Long Horizon Transformer Quantile Fault Prediction for Multi Site Industrial Predictive Maintenance

David J Poland, Daniele Ravi, Na Helian

Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning windows measured in days rather…

eess.IV2026

Reinforcing the Weakest Links: Modernizing SIENA with Targeted Deep Learning Integration

Riccardo Raciti, Lemuel Puglisi, Francesco Guarnera +2

Percentage Brain Volume Change (PBVC) derived from Magnetic Resonance Imaging (MRI) is a widely used biomarker of brain atrophy, with SIENA among the most established methods for i…

eess.IV2025

CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis

Alec Sargood, Lemuel Puglisi, James H. Cole +3

Synthesizing amyloid PET scans from the more widely available and accessible structural MRI modality offers a promising, cost-effective approach for large-scale Alzheimer's Disease…

eess.SP2024★ 1 cited

Industrial Machines Health Prognosis using a Transformer-based Framework

David J Poland, Lemuel Puglisi, Daniele Ravi

This article introduces Transformer Quantile Regression Neural Networks (TQRNNs), a novel data-driven solution for real-time machine failure prediction in manufacturing contexts. O…