state_space_modelsRecurrent / convolutional / state-space Translating between means of approximating time series dynamics 2016-04-05 – 2023-05-24State filtering for hidden Markov models Kalman and friends 2015-06-22 – 2023-05-24Belief propagation 2014-11-25 – 2023-05-17Method of Adjoints for differentiating through ODEs 2017-09-15 – 2023-05-15Recursive identification Learning forward dynamics by looking at time series. 2017-09-15 – 2023-04-16Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2023-03-24Variational message-passing algorithms in graphical models Cleaving reality at the joint, then summing it at the marginal 2014-11-25 – 2023-01-12Transforms of Gaussian noise Delta method, error propagation, unscented transform, Taylor expansion… 2014-11-25 – 2022-12-23Laplace approximations in inference Lightweight uncertainties, especially for heavy neural nets 2021-07-28 – 2022-09-06Gaussian belief propagation Least squares at maximal elaboration 2014-11-25 – 2022-09-01Factorial hidden Markov models 2022-08-29Elliptical belief propagation Generalized least generalized squares 2022-08-22 – 2022-08-23Integrated Nested Laplace Approximation 2021-07-28 – 2022-07-26Nested sampling 2022-05-16System identification using particle filters A.k.a. parameter estimation in data assimilation 2014-07-25 – 2022-05-04SLAM Simultaneous Location and Mapping 2014-11-25 – 2022-04-28Particle belief propagation Graphical inference using empirical distribution estimates 2014-07-25 – 2022-04-08Particle Markov Chain Monte Carlo Particle systems as MCMC proposals 2014-07-25 – 2022-04-08Change points Looking for regime changes in stochastic processes. a.k.a. Switching state space models 2021-11-29 – 2022-04-01Gaussian processes on lattices 2019-10-30 – 2022-02-28Variational state filtering 2018-03-19 – 2021-12-08Gaussian Processes as stochastic differential equations Imposing time on things 2019-09-18 – 2021-11-25Approximate Bayesian Computation Posterior updates without likelihood 2020-08-25 – 2021-09-20Spectral factorization 2021-05-05 – 2021-05-07Wiener-Hopf method Righteous hack for certain integral equations 2021-05-05Random fields as stochastic differential equations Precision vs covariance, fight! 2020-10-12 – 2021-03-01Feynman-Kac formulae 2021-01-27Probabilistic spectral analysis 2019-11-13 – 2020-11-25Defining dynamics via Gaussian processes 2019-09-18
Recurrent / convolutional / state-space Translating between means of approximating time series dynamics 2016-04-05 – 2023-05-24
Recursive identification Learning forward dynamics by looking at time series. 2017-09-15 – 2023-04-16
Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2023-03-24
Variational message-passing algorithms in graphical models Cleaving reality at the joint, then summing it at the marginal 2014-11-25 – 2023-01-12
Transforms of Gaussian noise Delta method, error propagation, unscented transform, Taylor expansion… 2014-11-25 – 2022-12-23
Laplace approximations in inference Lightweight uncertainties, especially for heavy neural nets 2021-07-28 – 2022-09-06
System identification using particle filters A.k.a. parameter estimation in data assimilation 2014-07-25 – 2022-05-04
Particle belief propagation Graphical inference using empirical distribution estimates 2014-07-25 – 2022-04-08
Change points Looking for regime changes in stochastic processes. a.k.a. Switching state space models 2021-11-29 – 2022-04-01
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