Reference Identification

[Jacob-Stevens-Haas]

Notes to self to follow up on from Nathan's edits.

First, some references made it into the .tex that don't have .bib entries, and which I can't identify:

• Bayesian PDE discovery from data~\cite{atkinson2020bayesian}

  • Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data
  • Data-driven discovery of free-form governing differential equations
  • Structured Bayesian Gaussian process latent variable model: Applications to data-driven dimensionality reduction and high-dimensional inversion

• symbolic learning on graph neural networks~\cite{cranmer2019learning,cranmer2020discovering

  • Miles Cranmer from Princeton?
  • Kyle Cranmer from University of Wisconsin?

• Also symbolic graph neural networks: sanchez2020learning

Other:

• Removal of lines 50-54?
• This comment:

  do we use the methods [van Breugel, Barratt] in these papers? if so, you can say, these devleopments are helpful in the parameter search; otherwise i would decrease editorial comments. We use the latter

• This comment:

  i'd say a but more about the structure of G here and leave the comment about heuristic experience for results or discussion.

[Jacob-Stevens-Haas]

Done