Selected publications
FreqAI: generalizing adaptive modeling for chaotic time-series market forecasts

Robert A. Caulk, Elin Törnquist, Matthias Voppichler, Andrew R. Lawless, Ryan McMullan, Wagner Costa Santos, Timothy C. Pogue, Johan van der Vlugt, Stefan P. Gehring, and Pascal Schmidt
Journal of Open Source Software, Volume 7(80) (2022), 4864, doi:10.21105/joss.04864

Training Deep Surrogate Models with Large Scale Online Learning

Lucas T. Meyer, Marc Schouler, Robert A. Caulk, Alejandro Ribes, and Bruno Raffin
International Conference for Machine Learning 2023. Submitted in Review

Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses

Marc Schouler, Robert A. Caulk, Lucas T. Meyer, Bruno Raffin, et al.
Journal of Open Source Software Submitted in Review

Driving adaptive modeling with data science

Robert A. Caulk, and Elin Törnquist
Data Science Guest Lecture, Cardiff Metropolitan University, 2022-11-21

Calcul distribué MPI pour la dynamique de systèmes particulaires (MPI distributed computing for dynamic particulate systems)

Bruno Chareyre, Robert A. Caulk, William Chevremont, Thomas Guntz, François Kneib, Deepak Kunhappen, Jean Pourroy
Yade Technical Archive (2019)

Accelerating Yade’s poromechanical coupling with matrix factorization reuse, parallel task management, and GPU computing

Robert A. Caulk, Emanuele Catalano, and Bruno Chareyre
Computer Physics Communications, Volume 248 (2020), 106991, doi:10.1016/j.cpc.2019.106991

A pore-scale thermo–hydro-mechanical model for particulate systems

Robert Caulk, Luc Scholtès, Marek Krzaczek, and Bruno Chareyre
Computer Methods in Applied Mechanics and Engineering, Volume 372 (2020), 113292, doi:10.1016/j.cma.2020.113292