Remaining useful life Prediction of air spring. - Farzaneh Ahmadzadeh; Jonas Biteus; Olof Steinert (ICPHM, 2019)

Low dimensional synthetic data generation for improving data driven prognostic models. - Tony Lindgren; Olof Steinert (ICPHM, 2022)

Knowledge Transfer in Engineering Fleets: Hierarchical Bayesian Modelling for Multi-Task Learning. - Lawrence A. Bull; Maharshi Harshadbhai Dhada; Olof Steinert; Tony Lindgren; Ajith Kumar Parlikad; Andrew B. Duncan; Mark Girolami (CoRR, 2022)

Automotive Multilingual Fault Diagnosis. - John Pavlopoulos; Alv Romell; Jacob Curman; Olof Steinert; Tony Lindgren; Markus Borg (CoRR, 2022)

Robust Contrastive Learning and Multi-shot Voting for High-dimensional Multivariate Data-driven Prognostics. - Kaiji Sun; Sindri Magnússon; Olof Steinert; Tony Lindgren (ICPHM, 2023)

Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning. - Lawrence A. Bull; Domenic Di Francesco; Maharshi Harshadbhai Dhada; Olof Steinert; Tony Lindgren; Ajith Kumar Parlikad; Andrew B. Duncan; Mark Girolami (Comput. Aided Civ. Infrastructure Eng., 2023)

Weibull recurrent neural networks for failure prognosis using histogram data. - Maharshi Harshadbhai Dhada; Ajith Kumar Parlikad; Olof Steinert; Tony Lindgren (Neural Comput. Appl., 2023)

SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance. - Zahra Kharazian; Tony Lindgren; Sindri Magnússon; Olof Steinert; Oskar Andersson Reyna (CoRR, 2024)

A Cost-Sensitive Transformer Model for Prognostics Under Highly Imbalanced Industrial Data. - Ali Beikmohammadi; Mohammad Hosein Hamian; Neda Khoeyniha; Tony Lindgren; Olof Steinert; Sindri Magnússon (CoRR, 2024)

Automotive fault nowcasting with machine learning and natural language processing. - John Pavlopoulos; Alv Romell; Jacob Curman; Olof Steinert; Tony Lindgren; Markus Borg; Korbinian Randl (Mach. Learn., 2024)