Computer vision-based framework for extracting geological lineaments from optical remote sensing data. - Ehsan Farahbakhsh; Rohitash Chandra; Hugo K. H. Olierook; Richard Scalzo; Chris Clark; Steven M. Reddy; R. Dietmar Müller (CoRR, 2018)

Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. - Richard Scalzo; David Kohn; Hugo K. H. Olierook; Gregory Houseman; Rohitash Chandra; Mark A. Girolami; Sally Cripps (CoRR, 2018)

Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. - Jodie Pall; Rohitash Chandra; Danial Azam; Tristan Salles; Jody M. Webster; Richard Scalzo; Sally Cripps (Environ. Model. Softw., 2020)

Volume and uncertainty estimates of on-farm reservoirs using surface reflectance and LiDAR data. - Ignacio Fuentes; Richard Scalzo; R. Willem Vervoort (Environ. Model. Softw., 2021)

Semi-Supervising an Anomalous Universe. - David Sweeney; Alberto Krone-Martins; Peter Tuthill; Richard Scalzo (e-Science, 2023)

PINN-Ray: A Physics-Informed Neural Network to Model Soft Robotic Fin Ray Fingers. - Xing Wang 016; Joel Janek Dabrowski; Joshua Pinskier; Lois Liow; Vinoth Viswanathan; Richard Scalzo; David Howard 001 (IROS, 2024)

Emergence of Computational Structure in a Neural Network Physics Simulator. - Rohan Hitchcock; Gary W. Delaney; Jonathan H. Manton; Richard Scalzo; Jingge Zhu (CoRR, 2025)