Efficient training of interval Neural Networks for imprecise training data. - Jonathan Sadeghi; Marco de Angelis 002; Edoardo Patelli (Neural Networks, 2019)

Uncertainty modelling for scarce and imprecise data in engineering applications. - Jonathan Sadeghi (2020)

A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation. - Jonathan Sadeghi; Blaine Rogers; James Gunn; Thomas Saunders; Sina Samangooei; Puneet Kumar Dokania; John Redford (CoRR, 2021)

Perspectives on the system-level design of a safe autonomous driving stack. - Majd Hawasly; Jonathan Sadeghi; Morris Antonello; Stefano V. Albrecht; John Redford; Subramanian Ramamoorthy (AI Commun., 2022)

Bayesian Quadrature for Probability Threshold Robustness of Partially Undefined Functions. - Jonathan Sadeghi; Romain Mueller; John Redford (CoRR, 2022)

Query-Based Hard-Image Retrieval for Object Detection at Test Time. - Edward Ayers; Jonathan Sadeghi; John Redford; Romain Mueller; Puneet K. Dokania (AAAI, 2023)

Attacking Motion Planners Using Adversarial Perception Errors. - Jonathan Sadeghi; Nicholas A. Lord; John Redford; Romain Mueller (CoRR, 2023)

On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines. - Selim Kuzucu; Kemal Oksuz; Jonathan Sadeghi; Puneet K. Dokania (ECCV (21), 2024)