Signal processing

Branding exercise within statistics and functional analysis focussing on the tricks that are most marketable to telecommunications firms.

Voice transcriptions and speech recognition 2019-01-08 – 2023-12-05

Audiobooks Long form podcasts 2014-11-11 – 2023-12-02

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

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

Calibration of probabilistic forecasts Proper scoring rules, skill scores etc 2015-06-16 – 2023-11-15

Feedback system identification, not necessarily linear Learning dynamics from data 2016-08-01 – 2023-11-15

Non-negative matrix factorisation 2019-10-14 – 2023-10-26

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

Low-rank matrices 2014-08-05 – 2023-09-29

Matrix inverses 2014-08-05 – 2023-09-29

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

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

Orthonormal and unitary matrices Energy preserving operators, generalized rotations 2019-10-22 – 2023-09-19

Nearly-low-rank Hermitian matrices a.k.a. perturbations of the identity, low-rank-plus-diagonal matrices 2014-08-05 – 2023-09-13

Code generation, programming assistants 2021-10-14 – 2023-08-28

Approximate matrix factorisations and decompositions Sometimes even exact 2014-08-05 – 2023-08-23

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

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

Reinforcement learning 2014-11-27 – 2023-07-17

Rough path theory and signature methods 2021-04-02 – 2023-06-29

Neural nets with implicit layers Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem 2020-12-08 – 2023-06-28

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

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

Recurrent / convolutional / state-space Translating between means of approximating time series dynamics 2016-04-05 – 2023-05-24

State filtering for hidden Markov models Kalman and friends 2015-06-22 – 2023-05-24

Singular Value Decomposition The ML workhorse 2014-08-05 – 2023-05-23

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

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

Method of Adjoints for differentiating through ODEs 2017-09-15 – 2023-05-15

Matrix square roots Whitening, preconditioning etc 2014-08-05 – 2023-05-13

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

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

Data summarization On maps drawn at smaller than 1:1 scale 2019-01-14 – 2023-04-27

Recursive identification Learning forward dynamics by looking at time series. 2017-09-15 – 2023-04-16

Optimal rotations 2021-05-18 – 2023-04-06

MLP-Mixer neural networks 2021-11-21 – 2023-03-30

Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2023-03-24

Practical text generation and writing assistants 2019-01-08 – 2023-03-23

Ensemble Kalman methods Data Assimilation; Data fusion; Sloppy filters for over-ambitious models 2015-06-22 – 2023-03-18

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

The Matrix-Gaussian distribution 2022-08-19 – 2023-02-16

Variational message-passing algorithms in graphical models Cleaving reality at the joint, then summing it at the marginal 2014-11-25 – 2023-01-12

Elliptical distributions 2015-06-23 – 2023-01-03

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

Randomised linear algebra 2016-08-16 – 2022-10-22

Online learning 2018-09-30 – 2022-10-20

Forecasting Vegan haruspicy 2015-06-16 – 2022-10-08

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

Ensemble Kalman methods for training neural networks Data assimilation for network weights 2022-09-20

Penalised/regularised regression 2016-06-23 – 2022-09-19

Laplace approximations in inference Lightweight uncertainties, especially for heavy neural nets 2021-07-28 – 2022-09-06

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

Scattering transforms 2022-03-16 – 2022-08-31

Factorial hidden Markov models 2022-08-29

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

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

Neural nets with implicit layers Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem 2020-12-08 – 2022-08-09

Learning Gamelan 2016-04-05 – 2022-08-05

Neural learning for spatiotemporal systems 2020-09-16 – 2022-07-28

Integrated Nested Laplace Approximation 2021-07-28 – 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

Markov decision problems 2014-11-27 – 2022-06-07

Stochastic partial differential equations SDEs taking values in some function space 2021-01-27 – 2022-05-25

Nested sampling 2022-05-16

System identification using particle filters A.k.a. parameter estimation in data assimilation 2014-07-25 – 2022-05-04

Forecasting with model averaging Mixture of experts, ensembles and time series 2022-05-04

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

Synchrony between things, especially organisms Entrainment, synchronisation, dancing together 2014-11-03 – 2022-04-23

Beta Processes 2019-10-14 – 2022-04-08

Stationary Gamma processes 2019-10-14 – 2022-04-08

Particle belief propagation Graphical inference using empirical distribution estimates 2014-07-25 – 2022-04-08

Particle Markov Chain Monte Carlo Particle systems as MCMC proposals 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

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

Multivariate Gamma distributions 2019-10-14 – 2022-03-14

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

Fun with rotational symmetries 2021-01-29 – 2022-03-03

Gaussian processes on lattices 2019-10-30 – 2022-02-28

Audio sample management 2021-09-14 – 2022-02-19

Visual node based programming a.k.a. dataflow graphs, patchers, visual coding, flow-based programming 2020-06-13 – 2022-02-12

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

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

Running neural nets backwards 2022-01-29

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

Faust, the DSP language 2016-08-22 – 2022-01-16

Matrix-valued random variates 2021-12-01 – 2022-01-06

Music software frameworks and programming languages, for music 2016-08-22 – 2022-01-05

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

Variational state filtering 2018-03-19 – 2021-12-08

Random rotations 2021-05-18 – 2021-12-01

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

Convolutional neural networks 2017-11-10 – 2021-11-21

High dimensional statistics 2015-03-12 – 2021-10-28

Neural music synthesis 2016-01-15 – 2021-10-14

Fractals and self-similarity 2011-11-13 – 2021-09-22

Approximate Bayesian Computation Posterior updates without likelihood 2020-08-25 – 2021-09-20

Software audio routers Patch cables for the cable-shy 2017-06-03 – 2021-09-08

Software video routers 2017-06-03 – 2021-09-08

Recurrent neural networks 2016-06-16 – 2021-09-06

Stochastic calculus Itô and friends 2019-09-19 – 2021-08-31

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

Backward stochastic differential equations 2019-09-19 – 2021-06-22

Stochastic differential equations 2019-09-19 – 2021-06-22

Voice fakes 2018-09-06 – 2021-06-17

Organising a music collection Also guessing missing metadata 2020-01-03 – 2021-06-14

Isotropic random vectors 2011-08-10 – 2021-05-24

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

Randomized low dimensional projections 2021-03-12 – 2021-05-24

Stochastic Taylor expansion Polynomial approximations of small randomnesses, Itô’s lemma 2020-10-15 – 2021-05-14

Spectral factorization 2021-05-05 – 2021-05-07

Wiener-Hopf method Righteous hack for certain integral equations 2021-05-05

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

Random fields as stochastic differential equations Precision vs covariance, fight! 2020-10-12 – 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

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

Auditory features descriptors, maps, representations for audio 2019-11-13 – 2021-01-14

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

Probabilistic spectral analysis 2019-11-13 – 2020-11-25

Observability and sensitivity in learning dynamical systems Parameter identifiability in dynamical models 2020-11-09

Weighted data in statistics 2020-11-04 – 2020-11-06

Audiovisuals Synesthetic and other cross-media audio stunts 2020-10-26

Bandit problems Also stochastic control 2014-11-27 – 2020-10-16

Sparse model selection 2016-09-05 – 2020-10-02

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

Music software 2014-11-11 – 2020-09-07

Long memory time series 2011-11-13 – 2020-05-28

Malliavin calculus 2020-05-23 – 2020-05-25

Lévy stochastic differential equations 2020-05-23

Analysis/resynthesis of audio 2016-01-15 – 2020-04-09

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

Effective sample size 2016-11-21 – 2020-03-03

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

Audio source separation 2019-11-04 – 2019-11-26

Machine listening Statistical models for audio 2014-10-10 – 2019-11-12

ISMIR 2019 Music Nerds in Delft 2019-11-04 – 2019-11-09

Optimal control 2015-06-22 – 2019-11-01

Sparse regression 2016-06-23 – 2019-10-24

Rhythm Especially for generative music 2014-11-03 – 2019-10-23

Delays and reverbs for audio processing …ing …ing …ing 2015-11-11 – 2019-10-22

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

Zeros of random trigonometric polynomials 2019-05-20 – 2019-10-14

Random (element) matrix theory 2014-11-09 – 2019-10-10

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

Defining dynamics via Gaussian processes 2019-09-18

Fourier interpolation 2019-06-19

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

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

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

Matlab A method of charging you licensing fees to use the CPU you already bought 2016-06-13 – 2017-12-13

Compressed sensing and sampling A fancy ways of counting zero 2014-08-18 – 2017-06-14

Greatest hits 2016-11-19 – 2016-12-12

Blind deconvolution 2015-03-01 – 2016-07-27

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

Function approximation and interpolation 2016-06-09

Deconvolution 2015-04-19 – 2016-04-11

How to make crazy experiment on sound design (sic) 2015-09-17

Stream processing and reactive programming 2014-10-30 – 2015-07-01