gp

Neural process regression 2019-12-03 – 2023-11-28

Large sample theory 2015-02-15 – 2023-08-02

Gaussian process regression And classification. And extensions. 2019-12-03 – 2023-07-28

Python spatial statistics 2020-09-11 – 2023-07-26

The Gaussian distribution The default probability distribution 2016-06-27 – 2023-07-19

Geoscience 2020-09-11 – 2023-07-19

Gaussian process ensembles Bayesian committee machines, product-of-experts 2023-07-12

Spatial data in R 2021-03-21 – 2023-06-13

Bayes functional regression 2019-12-03 – 2023-05-25

Belief propagation 2014-11-25 – 2023-05-17

Distances between Gaussian distributions Nearly equivalent to distances between symmetric positive definite matrices 2016-06-27 – 2023-05-03

Transforms of Gaussian noise Delta method, error propagation, unscented transform, Taylor expansion… 2014-11-25 – 2022-12-23

Neural tangent kernel 2020-12-09 – 2022-10-14

Gaussian process inference by partial updates 2020-12-03 – 2022-09-22

Posterior Gaussian process samples by updating prior samples Matheron’s other weird trick 2020-12-03 – 2022-09-20

Gaussian belief propagation Least squares at maximal elaboration 2014-11-25 – 2022-09-01

Elliptical belief propagation Generalized least generalized squares 2022-08-22 – 2022-08-23

Gaussian process regression software And classification. 2019-12-03 – 2022-07-29

Bayes linear regression and basis-functions in Gaussian process regression a.k.a Fixed Rank Kriging, weight space GPs 2022-02-22 – 2022-07-27

Simulating Gaussian processes on a lattice 2022-03-17 – 2022-07-26

SLAM Simultaneous Location and Mapping 2014-11-25 – 2022-04-28

Vecchia factoring of GP likelihoods Ignore some conditioning in the dependencies and attain a sparse cholesky factor for the precision matrix 2022-04-27

Bayesian nonparametric statistics Updating more dimensions than datapoints 2016-05-30 – 2022-04-07

Simulating Gaussian processes 2022-03-17

Learning Gaussian processes which map functions to functions 2020-12-07 – 2022-02-25

Karhunen-Loève expansions 2019-09-16 – 2022-02-01

Spatial processes and statistics thereof 2011-07-29 – 2022-01-28

Learning on manifolds Finding the lowest bit of a krazy straw, from the inside 2011-10-21 – 2022-01-26

Multi-output Gaussian process regression 2020-12-02 – 2021-11-26

Gaussian Processes as stochastic differential equations Imposing time on things 2019-09-18 – 2021-11-25

t-processes, t-distributions 2021-11-10 – 2021-11-24

Fun with determinants Especially Jacobian determinants 2011-04-06 – 2021-10-12

Vector Gaussian processses 2020-12-02 – 2021-08-16

Convolutional stochastic processes Moving averages of noise 2021-03-01 – 2021-08-16

Gaussian processes 2016-08-07 – 2021-06-23

Deep Gaussian process regression 2021-05-13

Infinite width limits of neural networks 2020-12-09 – 2021-05-11

Convolutional Gaussian processes 2021-03-01

Stochastic processes on manifolds 2021-03-01

Efficient factoring of GP likelihoods 2020-10-16 – 2020-10-26

GP inducing features 2020-10-16 – 2020-10-26

GP inducing variables 2020-10-16 – 2020-10-26

Localized Gaussian processes 2020-10-16 – 2020-10-26

Statistics of spatio-temporal processes 2020-09-11 – 2020-09-11

Defining dynamics via Gaussian processes 2019-09-18