Small Group Learning Activities in Systems and Control Theory using Fidget Cars. - Laura E. Ray; David Hodgson; David Feinauer; Raina White; Annett Gawerc; Prudence Merton; Devin Montgomery; Blair Allison; Nathan Amanquah; Charles Jackson; Fred McBagonluri; Paul Shiue; et al. (ACC, 2018)

An O(log2 N) SMC2 Algorithm on Distributed Memory with an Approx. Optimal L-Kernel. - Conor Rosato; Alessandro Varsi; Joshua Murphy; Simon Maskell (SDF-MFI, 2023)

Detecting Facial Landmarks on 3D Models Based on Geometric Properties - A Review of Algorithms, Enhancements, Additions and Open-Source Implementations. - Oguzhan Topsakal; Tahir Cetin Akinci; Joshua Murphy; Taylor Lee-James Preston; Mehmet Mazhar Çelikoyar (IEEE Access, 2023)

Parameterizing Hierarchical Particle Filters with Concept Drift for Time-varying Parameter Estimation. - Joshua Murphy; Conor Rosato; Andrew Millard; Simon Maskell (APSIPA, 2024)

Enhanced SMC2: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals. - Conor Rosato; Joshua Murphy; Alessandro Varsi; Paul R. Horridge; Simon Maskell (MFI, 2024)

Recent User Interface and Experience Development in Virtual Reality: A Literature Study. - Joshua Murphy; Abdelwahab Hamam (HCI (23), 2025)

Incorporating the ChEES Criterion into Sequential Monte Carlo Samplers. - Andrew Millard; Joshua Murphy; Daniel Frisch; Simon Maskell (CoRR, 2025)

Utilising Gradient-Based Proposals Within Sequential Monte Carlo Samplers for Training of Partial Bayesian Neural Networks. - Andrew Millard; Joshua Murphy; Simon Maskell; Zheng Zhao (CoRR, 2025)

Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles. - Andrew Millard; Zheng Zhao; Joshua Murphy; Simon Maskell (CoRR, 2025)

Hess-MC2: Sequential Monte Carlo Squared using Hessian Information and Second Order Proposals. - Joshua Murphy; Conor Rosato; Andrew Millard; Lee Devlin; Paul R. Horridge; Simon Maskell (CoRR, 2025)