# time_series

Audio/music corpora
Smells like Team Audioset
2014-08-08
– 2023-12-06Voice transcriptions and speech recognition
2019-01-08
– 2023-12-05System identification in continuous time
Learning in continuous ODEs, SDEs and CDEs
2016-08-01
– 2023-11-30Neural process regression
2019-12-03
– 2023-11-28Simulation-based inference
2014-12-23
– 2023-11-23Machine learning for partial differential equations
2017-05-15
– 2023-11-17Calibration of probabilistic forecasts
Proper scoring rules, skill scores etc
2015-06-16
– 2023-11-15Feedback system identification, not necessarily linear
Learning dynamics from data
2016-08-01
– 2023-11-15Physics-informed neural networks
2019-10-15
– 2023-10-19Neural PDE operator learning
Especially forward operators. Image-to-image regression, where the images encode a physical process.
2019-10-15
– 2023-10-19Probabilistic numerics
2023-07-13
– 2023-09-25Machine learning for climate systems
2020-04-02
– 2023-09-25Orthonormal and unitary matrices
Energy preserving operators, generalized rotations
2019-10-22
– 2023-09-19Code generation, programming assistants
2021-10-14
– 2023-08-28Generalised autoregressive processes
2022-01-10
– 2023-08-11Materials informatics
Machine learning in condensed matter physics, chemistry and materials science
2023-08-01
– 2023-08-08Non-uniform signal sampling
Discrete sample representation of continuous signals without a grid
2019-01-08
– 2023-08-08Gaussian process regression
And classification. And extensions.
2019-12-03
– 2023-07-28Python spatial statistics
2020-09-11
– 2023-07-26Geoscience
2020-09-11
– 2023-07-19Rough path theory and signature methods
2021-04-02
– 2023-06-29Decaying sinusoid dictionaries
2019-01-07
– 2023-06-15Noise contrastive estimation
Also “negative sampling”.
2020-04-22
– 2023-06-06Bayes functional regression
2019-12-03
– 2023-05-25Non-Gaussian Bayesian functional regression
2019-10-10
– 2023-05-25Recurrent / 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
– 2023-05-24Neural learning dynamical systems
2018-08-13
– 2023-05-23Belief propagation
2014-11-25
– 2023-05-17Method of Adjoints for differentiating through ODEs
2017-09-15
– 2023-05-15Multi-objective optimisation
2021-07-14
– 2023-05-04Recursive 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
– 2023-03-24Transformer networks
The transformer-powered subtitle for this article is “Our most terrifyingly effective weapon against the forces of evil is our ability to laugh at them.”
2017-12-20
– 2023-03-22Ensemble Kalman methods
Data Assimilation; Data fusion; Sloppy filters for over-ambitious models
2015-06-22
– 2023-03-18Variational 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
– 2022-12-23Machine learning for physical sciences
Turbulent mixing at the boundary between disciplines with differing inertia and viscosity
2017-05-15
– 2022-12-07COVID-19 in practice
SARS-CoV-2 to its friends
2020-11-25
– 2022-12-07Density ratio tricks
2022-12-06Online learning
2018-09-30
– 2022-10-20Forecasting
Vegan haruspicy
2015-06-16
– 2022-10-08The interpretation of RV densities as point process intensities and vice versa
Point process of observations ↔ observation of a point process
2016-09-13
– 2022-09-24Gaussian process inference by partial updates
2020-12-03
– 2022-09-22Generalised Ornstein-Uhlenbeck processes
Markov/AR(1)-like processes
2022-01-10
– 2022-09-21Conditional expectation and probability
2020-02-04
– 2022-09-21Posterior Gaussian process samples by updating prior samples
Matheron’s other weird trick
2020-12-03
– 2022-09-20Ensemble Kalman methods for training neural networks
Data assimilation for network weights
2022-09-20Gaussian belief propagation
Least squares at maximal elaboration
2014-11-25
– 2022-09-01State space reconstruction
2014-10-13
– 2022-08-30Factorial hidden Markov models
2022-08-29Elliptical belief propagation
Generalized least generalized squares
2022-08-22
– 2022-08-23Gaussian process regression software
And classification.
2019-12-03
– 2022-07-29Neural learning for spatiotemporal systems
2020-09-16
– 2022-07-28Gamma distributions
2019-10-14
– 2022-07-27Simulating Gaussian processes on a lattice
2022-03-17
– 2022-07-26Stochastic signal sampling
Discrete sample representation of continuous stochastic processes
2017-05-30
– 2022-06-24Signal sampling
Discrete representation of continuous signals and converse
2017-05-30
– 2022-06-24Markov decision problems
2014-11-27
– 2022-06-07Stochastic partial differential equations
SDEs taking values in some function space
2021-01-27
– 2022-05-25Nested sampling
2022-05-16System identification using particle filters
A.k.a. parameter estimation in data assimilation
2014-07-25
– 2022-05-04Forecasting with model averaging
Mixture of experts, ensembles and time series
2022-05-04SLAM
Simultaneous Location and Mapping
2014-11-25
– 2022-04-28Divisible, decomposable and stable distributions
Ways of slicing randomness
2017-06-15
– 2022-04-18Beta Processes
2019-10-14
– 2022-04-08Stationary Gamma processes
2019-10-14
– 2022-04-08Particle 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
– 2022-04-08Beta and Dirichlet distributions
2019-10-14
– 2022-04-04Change points
Looking for regime changes in stochastic processes. a.k.a. Switching state space models
2021-11-29
– 2022-04-01Simulating Gaussian processes
2022-03-17Survival analysis and reliability
Hazard rates, proportional hazard regression, life testing, mean time to failure
2019-03-12
– 2022-03-07Lévy Gamma processes
2019-10-14
– 2022-03-03Gaussian processes on lattices
2019-10-30
– 2022-02-28OODA loops
2021-05-01
– 2022-02-28Learning Gaussian processes which map functions to functions
2020-12-07
– 2022-02-25Ergodicity and mixing
Things that probably happen eventually on average
2011-10-17
– 2022-02-13Learning on manifolds
Finding the lowest bit of a krazy straw, from the inside
2011-10-21
– 2022-01-26Feedback system identification, linear
2016-07-27
– 2022-01-21Gamma-Beta algebra
2019-10-14
– 2022-01-12Variational state filtering
2018-03-19
– 2021-12-08Convolutional subordinator processes
2021-03-08
– 2021-12-01Multi-output Gaussian process regression
2020-12-02
– 2021-11-26Gaussian Processes as stochastic differential equations
Imposing time on things
2019-09-18
– 2021-11-25t-processes, t-distributions
2021-11-10
– 2021-11-24Fractals and self-similarity
2011-11-13
– 2021-09-22Approximate Bayesian Computation
Posterior updates without likelihood
2020-08-25
– 2021-09-20Recurrent neural networks
2016-06-16
– 2021-09-06Path smoothness properties of stochastic processes
Continuity, differentiability and other smoothness properties
2020-02-26
– 2021-09-02Stochastic calculus
Itô and friends
2019-09-19
– 2021-08-31Vector Gaussian processses
2020-12-02
– 2021-08-16Convolutional stochastic processes
Moving averages of noise
2021-03-01
– 2021-08-16Essays in stochastic processes
My PhD thesis with Zdravko I. Botev
2021-08-13Cascade models
a.k.a. cluster distributions, Galton-Watson models
2019-10-11
– 2021-08-04Contact tracing
Reverse engineering social graphs for the control of contagions of pathogens, subversive ideology and other substances of interest
2020-03-21
– 2021-07-28Contagion processes and their statistics
2016-08-30
– 2021-07-15Media virality
Strategic modelling for content creators
2016-08-30
– 2021-07-15Multi-task ML
2021-07-14Gaussian processes
2016-08-07
– 2021-06-23Backward stochastic differential equations
2019-09-19
– 2021-06-22Stochastic differential equations
2019-09-19
– 2021-06-22Voice fakes
2018-09-06
– 2021-06-17Stochastic Taylor expansion
Polynomial approximations of small randomnesses, Itô’s lemma
2020-10-15
– 2021-05-14Deep Gaussian process regression
2021-05-13Spectral factorization
2021-05-05
– 2021-05-07Wiener-Hopf method
Righteous hack for certain integral equations
2021-05-05Path integral formulations of SDEs
Feynman path integrals, esp for stochastic processes
2021-04-19Dynamical systems via Koopman operators
Composition operators, Dynamic Extended Mode decompositions…
2020-10-13
– 2021-04-09Convolutional Gaussian processes
2021-03-01Random fields as stochastic differential equations
Precision vs covariance, fight!
2020-10-12
– 2021-03-01Stochastic processes on manifolds
2021-03-01Feynman-Kac formulae
2021-01-27Probabilistic spectral analysis
2019-11-13
– 2020-11-25Observability and sensitivity in learning dynamical systems
Parameter identifiability in dynamical models
2020-11-09Time
Certain quirks of entropy
2020-10-20Splitting simulation
2017-05-29
– 2020-09-28Filter design, linear
Especially digital
2017-07-24
– 2020-09-18Statistics of spatio-temporal processes
2020-09-11
– 2020-09-11Functional regression
2016-01-05
– 2020-05-28Long memory time series
2011-11-13
– 2020-05-28Malliavin calculus
2020-05-23
– 2020-05-25Lévy stochastic differential equations
2020-05-23Queueing
The mathematical field whose major result is enraging you about call centres
2015-06-03
– 2020-04-06Epidemics
2020-03-10
– 2020-04-03Effective sample size
2016-11-21
– 2020-03-03Cepstral transforms and harmonic identification
2017-09-12
– 2020-02-13Random change of time
Stochastic processes derived by varying the rate of time’s passage, which is more convenient than I imagined
2015-08-05
– 2020-02-10Branching processes
2014-08-18
– 2020-02-07Hawkes processes
2019-12-22Cherchez la martingale
Stuff about probability and orthogonality
2019-11-25
– 2019-11-30Optimal control
2015-06-22
– 2019-11-01Delays and reverbs for audio processing
…ing …ing …ing
2015-11-11
– 2019-10-22Generalized Galton-Watson processes
2014-12-28
– 2019-10-11Statistical learning theory for time series
2016-11-03
– 2019-10-01Correlograms
Also covariances
2018-08-08
– 2019-09-22Defining dynamics via Gaussian processes
2019-09-18Sparse stochastic processes identification and sampling
Discrete sample representation of sparse continuous stochastic processes
2018-11-22
– 2018-10-29Signal processing
That which you study for 4 years in order to design trippy music visualisers
2015-03-18
– 2018-01-05Warping and registration problems
Matching up of bumps and wibbles in stretchy things
2016-08-17
– 2017-07-23Stochastic processes and fields
Probabilistic structures over index sets and state spaces
2014-08-05
– 2017-06-15Thermodynamics of life
2014-09-23
– 2017-05-30Granger causation/Transfer Entropy
2012-07-26
– 2017-05-04Fractional Brownian motion
2017-02-18Change of probability measure
2015-08-05
– 2016-08-16Dynamical systems
2016-04-26
– 2016-07-27Count time series models
2015-06-03
– 2015-12-09High frequency time series estimation
2016-06-12
– 2015-12-02Sigma algebras, probability spaces, measure theory
The scaffolding of randomness
2015-06-20Artificial chemistry
2011-12-13
– 2015-05-31Sparse regression for inhomogeneous Hawkes processes
My MSc thesis with Professors Didier Sornette and Sara van de Geer
2015-04-28
– 2015-05-12