Richard Scalzo

Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success pdf

Rohitash Chandra, Mark A. Girolami, Sally Cripps, 2018, Geoscientific Model Development.

Computer vision-based framework for extracting tectonic lineaments from optical remote sensing data

Rohitash Chandra, Chris Clark, R. Dietmar Müller, 2018, International Journal of Remote Sensing.

Into the Noddyverse: A massive data store of 3D geological models for Machine Learning & inversion applications

Guillaume Pirot, Jérémie Giraud, Mark Lindsay, 2021 .

Periodic Astrometric Signal Recovery Through Convolutional Autoencoders

Antonio Picariello, Massimo Brescia, Emille E. O. Ishida, 2021 .

Volume and uncertainty estimates of on-farm reservoirs using surface reflectance and LiDAR data

Richard Scalzo, Ignacio Fuentes, R. Willem Vervoort, 2021, Environ. Model. Softw..

Predictive control for adaptive optics using neural networks

Julien Lozi, Olivier Guyon, Peter G. Tuthill, 2021, Journal of Astronomical Telescopes, Instruments, and Systems.

Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models

Richard Scalzo, Ehsan Farahbakhsh, Rohitash Chandra, 2021 .