Accelerating Bayesian inference and early diagnostics for probabilistic models. I wrote this package both to accelerate my models and to test some methodological hypotheses.
Working out and benchmarking efficient invertible transforms from unconstrained to constrained spaces for probabilistic programming. See Stan implementations for probability vectors and for orthogonal matrices.
Interactive teaching resource on supervised learning, from linear regression to neural networks. Developed for the IntroML workshop series at the University of Tübingen.
