Links

Pointers to stuff I find interesting

  • The Spurious Correlations website by Tyler Vigen which computes pairwise correlations between about 25 thousand time-series to find the most surprising ones.
  • The 2025 ICLR blog post on sparse automatic differentiation by Adrian Hill, Guillaume Dalle and Alexis Montoison. Automatic differentiation is probably the most important advance behind deep learning: how good to find it here blended with ingenious ways to enhance code efficiency, the good old coloring problem, and, of course, the Julia language.
  • A blog post by Ro Jefferson about Restricted Boltzmann Machines and generating functions
  • Friederich Shuller’s course on Differential Geometry and General Relativity
  • David MacKay’s course on Information Theory
  • A talk by Tom Minka on Automatic Differentiation and Message Passing
  • A two-part talk by Hugo Touchette on Large Deviations of continuous-time continuous-space Markov Processes
  • Federico Ricchi Tersenghi’s lectures at the 2017 Boulder Summer School
  • Chris Rackauckas’ lecture series on scientific computing
  • Miles Stoudenmire’s introductory lectures on Tensor Networks