Investigate stochastic methods for Bayesian regression

[wcwitt]

So far we have been using direct methods for computing the logdet and related terms required for maximizing the Bayesian evidence. However, for very large matrices, it could be advantageous to try something else that would be more compatible with SGD-type optimizers. Some useful references

• https://discourse.julialang.org/t/the-fastest-way-to-calculate-matrix-inversion/62892/10
• https://ameli.github.io/imate/ComputeTraceOfInverse.html

[wcwitt]

I don't think we need this in this short/medium-term.