Smooth transforms of Gaussian noise Delta method, error propagation, unscented transform, Taylor expansion, in finite and inifinite dimensional spaces 2014-11-25 – 2022-05-12
System identification using particle filters A.k.a. parameter estimation in data assimilation 2014-07-25 – 2022-05-04
Saying “Bayes” is not enough Bayesians are usually not actually doing Bayesian reasoning well and even if we were, it would be insufficient to do science, or life 2016-05-30 – 2022-04-15
Laplace approximations in inference Lightweight uncertainties, especially for heavy neural nets 2021-07-28 – 2022-04-10
Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2022-04-10
Particle belief propagation Graphical inference using empirical distribution estimates 2014-07-25 – 2022-04-08
Probabilistic neural nets Bayesian and other probabilistic inference in overparameterized ML 2017-01-11 – 2022-04-07
Change points Looking for regime changes in stochastic processes. a.k.a. Switching state space models 2021-11-29 – 2022-04-01
Probabilistic programming Doing statistics using the tools of computer science 2019-10-02 – 2022-02-11
Reparameterization tricks in inference Pathwise gradient estimation, nNormalizing flows, invertible density models, inference by measure transport, low-dimensional coupling… 2018-04-04 – 2021-12-21
Monte Carlo gradient estimation Especially stochastic automatic differentiation 2020-09-30 – 2021-12-20
Gaussian Processes as stochastic differential equations Imposing time on things 2019-09-18 – 2021-11-25
Random fields as stochastic differential equations Precision vs covariance, fight! 2020-10-12 – 2021-03-01
Chaos expansions Polynomial chaos, generalized polynomial chaos, arbitrary chaos etc 2020-05-21 – 2021-02-15
Frequentist consistency of Bayesian methods TFW two flawed methods for understanding the world agree with at least each other 2016-04-12 – 2019-10-19