Example: continual learning on toy data

[runame]

Simple example showing continual learning with the Laplace approximation on toy data.

[aleximmer]

I plan to implement the following to functionalities together with #40:

• add online or keep_H to .fit(..)flag that maintains the Hessian approximation and can thus be used for continual learning
• add .log_prob(theta) as method to BaseLaplace which allows to compute the regularizer in a CL setting This should make simple CL approaches very easy to implement or would we need anything else? Like this, we can just do

  la = Laplace(model, ...)   # init to prior
  for task in tasks:
  optimize(loss(task) + la.log_prob(), theta)
  # optionally interleaved or after training:
  optimize(la.log_marginal_likelihood(), hyperparams)
  la.fit(task, online=True)

  Do you see potential problems with this?

[runame]

No, this looks exactly like what we need for an improved CL interface. I'll look into the details when the PR is ready.