Physics-Informed Machine Learning Modelling of RF-EMF Exposure in Massive MIMO Systems. - Samuel Bilson; Tian Hong Loh; Fabien Héliot; Andrew Thompson 014 (IEEE Access, 2024)

Analytical results for uncertainty propagation through trained machine learning regression models. - Andrew Thompson 014 (CoRR, 2024)

Trustworthy Artificial Intelligence in the Context of Metrology. - Tameem Adel; Sam Bilson; Mark Levene; Andrew Thompson 014 (CoRR, 2024)

Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches. - Mohammad Moulaeifard; Loic Coquelin; Mantas Rinkevicius; Andrius Solosenko; Oskar Pfeffer; Ciaran Bench; Nando Hegemann; Sara Vardanega; Manasi Nandi; Jordi Alastruey; Christian Heiss; Vaidotas Marozas; et al. (CoRR, 2025)

A metrological framework for uncertainty evaluation in machine learning classification models. - Samuel Bilson; Maurice Cox; Anna Pustogvar; Andrew Thompson 014 (CoRR, 2025)

Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks. - Ciaran Bench; Vivek Desai; Mohammad Moulaeifard; Nils Strodthoff; Philip J. Aston; Andrew Thompson 014 (CoRR, 2025)

Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects. - Reva Schwartz; Rumman Chowdhury; Akash Kundu; Heather Frase; Marzieh Fadaee; Tom David; Gabriella Waters; Afaf Taik; Morgan Briggs; Patrick Hall; Shomik Jain; Kyra Yee; et al. (CoRR, 2025)