Yes, another lesser-known (?) way of scaling GP regression: a committee of observation subsets (Cao and Fleet 2015; Deisenroth and Ng 2015; Rullière et al. 2018; Tresp 2000).
1 References
Cao, and Fleet. 2015. “Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions.”
Deisenroth, and Ng. 2015. “Distributed Gaussian Processes.” In Proceedings of the 32nd International Conference on Machine Learning.
Jimenez, and Katzfuss. 2023. “Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes.” In Proceedings of The 26th International Conference on Artificial Intelligence and Statistics.
Liu, Cai, Wang, et al. 2018. “Generalized Robust Bayesian Committee Machine for Large-Scale Gaussian Process Regression.”
Rullière, Durrande, Bachoc, et al. 2018. “Nested Kriging Predictions for Datasets with a Large Number of Observations.” Statistics and Computing.
Tresp. 2000. “A Bayesian Committee Machine.” Neural Computation.