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Welcome to my notebook!
I'm a data scientist who likes writing about machine learning, functional programming, and above all, mathematics.
I've reproduced a list of recent posts here for your reading pleasure:
Posts
- Online learning and FoReL - August 16, 2023
- Counterfactual regret minimization - July 30, 2023
- Recursion and fixed points - December 21, 2022
- The neural tangent kernel - July 10, 2022
- Neural network Gaussian process kernels - July 7, 2022
- Notes on generalization theory - July 1, 2022
- Replica symmetry breaking - June 26, 2022
- Sherrington-Kirkpatrick model and the replica method - June 16, 2022
- Particle MCMC methods - August 30, 2020
- Empirical inference in Pyro - August 27, 2020
- Dirichlet processes - August 16, 2020
- Stochastic gradient estimators - August 11, 2020
- Probabilistic effects programming with Pyro - July 30, 2020
- Probability sheaves - June 20, 2020
- Probability monads - June 14, 2020
- Kullback-Leibler divergence, categorically - June 1, 2020
- Entropy in information theory - May 30, 2020
- Thermometer continuations, part 2 - February 15, 2020
- Thermometer continuations, part 1 - February 12, 2020
- Algebraic effects and freeness - February 9, 2020
- Delimited continuations - February 3, 2020
- Langevin dynamics for Bayesian inference - January 29, 2020
- Dual numbers in autodifferentiation - January 25, 2020
- Optics in Haskell - January 23, 2020
- Profunctors are generalized functors - January 21, 2020
- Initial post - January 20, 2020
…or you can find more in the archives.