3 papers
cs.LG2026
When More Modalities Hurt: Modality Dropout for Heavy-Duty Vehicle Engine Diagnostics
Adeel Zafar, Slawomir Nowaczyk, Hamid Sarmadi +1
Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor telemetry with over 80% missing…
cs.AI2026
Bridging Forecast Accuracy and Inventory KPIs: A Simulation-Based Software Framework
So Fukuhara, Abdallah Alabdallah, Nuwan Gunasekara +1
Efficient management of spare parts inventory is crucial in the automotive aftermarket, where demand is highly intermittent and uncertainty drives substantial cost and service risk…
cs.AI2025
Neuroplasticity-inspired dynamic ANNs for multi-task demand forecasting
Mateusz Å»arski, SÅawomir Nowaczyk
This paper introduces a novel approach to Dynamic Artificial Neural Networks (D-ANNs) for multi-task demand forecasting called Neuroplastic Multi-Task Network (NMT-Net). Unlike con…