Variational Gaussian Process regression

October 16, 2020 — October 26, 2020

algebra
approximation
Gaussian
generative
graphical models
Hilbert space
kernel tricks
machine learning
networks
optimization
probability
statistics
Figure 1

Placeholder for variational approximation to Gaussian Processes.

1 References

Damianou, Titsias, and Lawrence. 2011. “Variational Gaussian Process Dynamical Systems.” In Advances in Neural Information Processing Systems 24.
Gal, and van der Wilk. 2014. “Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models - a Gentle Tutorial.” arXiv:1402.1412 [Stat].
Huggins, Campbell, Kasprzak, et al. 2018. “Scalable Gaussian Process Inference with Finite-Data Mean and Variance Guarantees.” arXiv:1806.10234 [Cs, Stat].
MacKay. 2002. “Gaussian Processes.” In Information Theory, Inference & Learning Algorithms.
Salimbeni, and Deisenroth. 2017. “Doubly Stochastic Variational Inference for Deep Gaussian Processes.” In Advances In Neural Information Processing Systems.
Salimbeni, Eleftheriadis, and Hensman. 2018. “Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models.” In International Conference on Artificial Intelligence and Statistics.