hilbert_space

System identification in continuous time Learning in continuous ODEs, SDEs and CDEs 2016-08-01 – 2023-11-30

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

Machine learning for partial differential equations 2017-05-15 – 2023-11-17

Physics-informed neural networks 2019-10-15 – 2023-10-19

Neural PDE operator learning Especially forward operators. Image-to-image regression, where the images encode a physical process. 2019-10-15 – 2023-10-19

Probabilistic numerics 2023-07-13 – 2023-09-25

Machine learning for climate systems 2020-04-02 – 2023-09-25

Generalised autoregressive processes 2022-01-10 – 2023-08-11

Non-uniform signal sampling Discrete sample representation of continuous signals without a grid 2019-01-08 – 2023-08-08

Polynomial bases 2021-01-29 – 2023-07-28

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

(Reproducing) kernel tricks 2014-08-18 – 2023-07-21

Geoscience 2020-09-11 – 2023-07-19

Hypothesis tests, statistical 2014-08-23 – 2023-07-18

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

Position encoding Also Fourier features 2021-01-21 – 2023-06-23

Decaying sinusoid dictionaries 2019-01-07 – 2023-06-15

Matrix norms, divergences, metrics 2016-06-03 – 2023-05-29

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

Non-Gaussian Bayesian functional regression 2019-10-10 – 2023-05-25

Neural learning dynamical systems 2018-08-13 – 2023-05-23

Canonical correlation 2014-08-23 – 2023-05-17

Maximum Mean Discrepancy 2016-08-21 – 2023-05-03

Combining kernels 2019-09-16 – 2023-05-02

Covariance estimation Esp Gaussian 2014-11-16 – 2023-04-26

(Nearly-)Convex relation of nonconvex problems 2018-04-04 – 2023-03-17

Sparse coding with learnable dictionaries 2014-11-17 – 2023-03-02

Tensor decompositions 2016-08-15 – 2023-02-21

Last-layer Bayes neural nets Bayesian and other probabilistic inference in overparameterized ML 2017-01-11 – 2023-02-09

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

Machine learning for physical sciences Turbulent mixing at the boundary between disciplines with differing inertia and viscosity 2017-05-15 – 2022-12-07

Deep learning as a dynamical system 2018-08-13 – 2022-10-30

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

Precision matrix estimation Especially Gaussain 2014-11-16 – 2022-10-04

(Weighted) least squares fits 2016-09-22 – 2022-10-04

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

Generalised Ornstein-Uhlenbeck processes Markov/AR(1)-like processes 2022-01-10 – 2022-09-21

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

Mellin transforms 2021-01-29 – 2022-08-28

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

Empirical mode decomposition Multiplying your exposure to uncertainty principles 2018-01-06 – 2022-07-12

Stochastic signal sampling Discrete sample representation of continuous stochastic processes 2017-05-30 – 2022-06-24

Signal sampling Discrete representation of continuous signals and converse 2017-05-30 – 2022-06-24

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

Detecting stationarity in stochastic processes Change-points, trends and transients 2021-11-29 – 2022-04-01

Simulating Gaussian processes 2022-03-17

Wiener-Khintchine representations Spectral representations of stochastic processes 2019-05-08 – 2022-03-11

Sparse coding Wavelets, matching pursuit, overcomplete dictionaries… 2014-11-17 – 2022-03-07

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

Neural nets with basis decomposition layers 2021-03-09 – 2022-02-01

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

Feedback system identification, linear 2016-07-27 – 2022-01-21

Time frequency analysis Multiplying your exposure to uncertainty principles 2018-01-06 – 2021-12-21

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

Multilinear algebra Outer products, tensors, einstein summation 2021-10-08

Fractional differential equations 2016-03-22 – 2021-09-13

Wirtinger calculus It’s not complicated / It’s complex 2019-05-08 – 2021-09-07

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

Neural net kernels 2019-09-16 – 2021-05-24

Transforms of random variates 2020-06-04 – 2021-05-14

Deep Gaussian process regression 2021-05-13

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

Fourier transforms 2021-01-29 – 2021-04-26

Dynamical systems via Koopman operators Composition operators, Dynamic Extended Mode decompositions… 2020-10-13 – 2021-04-09

Kernel zoo 2019-09-16 – 2021-03-30

Convolutional Gaussian processes 2021-03-01

Stochastic processes on manifolds 2021-03-01

Learning covariance functions Learning a family of covariances at once 2019-09-16 – 2021-03-01

Frames and Riesz bases Generalisations of orthogonal bases 2017-06-12 – 2021-02-24

Stability in linear dynamical systems This Bodes well 2019-07-19 – 2021-02-16

Chaos expansions Polynomial chaos, generalized polynomial chaos, arbitrary chaos etc 2020-05-21 – 2021-02-15

Integral transforms 2021-01-29 – 2021-01-30

Miscellaneous nonstationary kernels 2019-09-16 – 2021-01-21

Warping of stationary stochastic processes 2019-09-16 – 2021-01-21

Covariance functions Variograms, Mercer kernels, positive definite operators, spare reproducing kernels for that Hilbert space I bought on eBay real cheap 2019-09-16 – 2021-01-05

Tensor regression 2020-11-19

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

Filter design, linear Especially digital 2017-07-24 – 2020-09-18

Gaussian process quantile regression 2020-09-16

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

Functional regression 2016-01-05 – 2020-05-28

Lévy stochastic differential equations 2020-05-23

Restricted isometry properties Plus incoherence, irrepresentability, and other uncertainty bounds for a sparse world, and maybe frame theory, what’s that now? 2017-06-12 – 2020-03-09

Kernel approximation 2016-07-27 – 2020-03-06

Cepstral transforms and harmonic identification 2017-09-12 – 2020-02-13

Cherchez la martingale Stuff about probability and orthogonality 2019-11-25 – 2019-11-30

Phase retrieval I’ve got the power. / Like the crack of the whip/ I snap attack/ Front to back 2017-01-16 – 2019-11-07

Discrete time Fourier and related transforms Also, chirplets, z-transforms, chromatic derivatives… 2019-10-17 – 2019-10-17

Correlograms Also covariances 2018-08-08 – 2019-09-22

Defining dynamics via Gaussian processes 2019-09-18

Representer theorems 2019-09-16

Wiener theorem Now with bonus Bochner! 2019-05-08

Ordinary differential equations Thou, silent form, dost tease us out of thought / As doth eternity 2019-03-28

Inner product spaces The most highly developed theory of squaring things 2019-01-01 – 2019-02-11

Sparse stochastic processes identification and sampling Discrete sample representation of sparse continuous stochastic processes 2018-11-22 – 2018-10-29

Linear algebra If the thing is twice as big, the transformed version of the thing is also twice as big. {End} 2011-04-06 – 2018-08-07

Signal processing That which you study for 4 years in order to design trippy music visualisers 2015-03-18 – 2018-01-05

Quantum probability and quantum information, noncommutative probability 2016-10-16 – 2017-09-18

Uncertainty principles 2017-05-14

Functional equations Putting the funk in functions 2017-02-06 – 2017-02-19

Concatenative synthesis 2015-12-13 – 2017-01-16

Fast multipole methods 2016-08-18 – 2016-09-20

Dynamical systems 2016-04-26 – 2016-07-27

Function approximation and interpolation 2016-06-09