probabilistic_algorithms

Neural denoising diffusion models Denoising diffusion probabilistic models (DDPMs), score-based generative models, generative diffusion processes, neural energy models… 2021-11-11 – 2023-05-25
Normalizing flows Invertible density models, sounding clever by using the word diffeomorphism like a real mathematician 2018-04-04 – 2023-05-02
Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2023-03-24
Transport maps Inference by measure transport, low-dimensional coupling… 2018-04-04 – 2023-02-21
Change points Looking for regime changes in stochastic processes. a.k.a. Switching state space models 2021-11-29 – 2022-04-01
Variational inference On fitting something not too far from a pretty good model that is not too hard 2016-03-22 – 2022-02-10
Bootstrap Shuffling reality to produce your data 2014-11-26 – 2022-01-27
Bias reduction Estimating the bias of an estimator so as to subtract it off again 2020-02-26