dynamical_systems
Smooth transforms of Gaussian noise
Delta method, error propagation, unscented transform, Taylor expansion, in finite and inifinite dimensional spaces
2014-11-25
– 2022-05-12Ensemble Kalman methods
Sloppy filters for over-ambitious models
2015-06-22
– 2022-05-10Forecasting with model averaging
Mixture of experts, ensembles and time series
2022-05-04SLAM
Simultaneous Location and Mapping
2014-11-25
– 2022-04-28Synchrony between things, especially organisms
Entrainment, synchronisation, dancing together
2014-11-03
– 2022-04-23Divisible, decomposable and stable distributions
Ways of slicing randomness
2017-06-15
– 2022-04-18Generalised Ornstein-Uhlenbeck processes
AR(1)-like processes
2022-01-10
– 2022-04-17Particle 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
– 2022-04-08Orthonormal and unitary matrices
Energy preserving operators, generalized rotations
2019-10-22
– 2022-04-05Belief propagation
2014-11-25
– 2022-03-31Gaussian belief propagation
Least squares at maximal elaboration
2014-11-25
– 2022-03-28Reservoir Computing
2022-03-28Neural nets with implicit layers
Also, declarative networks
2020-12-08
– 2022-03-09Gaussian processes on lattices
2019-10-30
– 2022-02-28Deep learning as a dynamical system
2018-08-13
– 2022-02-22Stability in dynamical systems
Lyapunov exponents and ilk
2019-05-21
– 2022-02-22System identification in continuous time
Learning in continuous ODEs, SDEs and CDEs
2016-08-01
– 2022-02-15Ergodicity and mixing
Things that probably happen eventually on average
2011-10-17
– 2022-02-13Neural learning for spatiotemporal systems
2020-09-16
– 2022-02-02Neural nets for “implicit representations”
2021-01-21
– 2022-02-01Neural nets with basis decomposition layers
2021-03-09
– 2022-02-01Running neural nets backwards
2022-01-29Feedback system identification, not necessarily linear
Learning dynamics from data
2016-08-01
– 2022-01-27Feedback system identification, linear
2016-07-27
– 2022-01-21Stochastic partial differential equations
SDEs taking values in some function space
2021-01-27
– 2022-01-18Generalised autoregressive processes
2022-01-10Variational state filtering
2018-03-19
– 2021-12-08Gaussian Processes as stochastic differential equations
Imposing time on things
2019-09-18
– 2021-11-25Neural nets for “implicit representations”
2021-01-21
– 2021-11-16Networks and graphs, theory thereof
2014-11-24
– 2021-10-20Random neural networks
2017-02-17
– 2021-10-12Stochastic calculus
Itô and friends
2019-09-19
– 2021-08-31Rough path theory
Also, signatures.
2021-04-02
– 2021-08-05Backward stochastic differential equations
2019-09-19
– 2021-06-22Stochastic differential equations
2019-09-19
– 2021-06-22Voice fakes
2018-09-06
– 2021-06-17Limit Theorems
Asymptotic distributions of random processes
2014-11-25
– 2021-05-17Stochastic Taylor expansion
Polynomial approximations of small randomnesses
2020-10-15
– 2021-05-14Spectral factorization
2021-05-05
– 2021-05-07Wiener-Hopf method
Righteous hack for certain integral equations
2021-05-05Path integral formulations
Feynman path integrals, esp for stochastic processes
2021-04-19Prediction processes
Some kind of weird time series formalism
2021-04-09Dynamical systems via Koopman operators
Composition operators, Dynamic Extended Mode decompositions…
2020-10-13
– 2021-04-09Matrix measure concentration inequalities and bounds
2014-11-25
– 2021-03-08Measure concentration inequalities
On being 80% sure I am only 20% wrong
2014-11-25
– 2021-03-04Random fields as stochastic differential equations
Precision vs covariance, fight!
2020-10-12
– 2021-03-01Stability in linear dynamical systems
This Bodes well
2019-07-19
– 2021-02-16Statistical mechanics of statistics
2016-12-01
– 2021-01-06Nonparametrically learning dynamical systems
2018-08-13
– 2020-12-08Probabilistic spectral analysis
2019-11-13
– 2020-11-25Observability and sensitivity in learning dynamical systems
Parameter identifiability in dynamical models
2020-11-09Filter design, linear
Especially digital
2017-07-24
– 2020-09-18Online learning
2018-09-30
– 2020-08-26Stochastic signal sampling
Discrete sample representation of continuous stochastic processes
2017-05-30
– 2020-06-11Functional regression
2016-01-05
– 2020-05-28Malliavin calculus
2020-05-23
– 2020-05-25Lévy stochastic differential equations
2020-05-23Effective sample size
2016-11-21
– 2020-03-03Cepstral transforms and harmonic identification
2017-09-12
– 2020-02-13Potential theory in probability
Something about harmonic functions or whatever
2020-02-12Infinitesimal generators
Generators of the transition semi-group, connection to Kolmogorov forward equations
2017-05-29
– 2020-02-05Non-uniform signal sampling
Discrete sample representation of continuous signals without a grid
2019-01-08
– 2019-12-03Convergence of random variables
2019-12-03Cherchez la martingale
Stuff about probability and orthogonality
2019-11-25
– 2019-11-30Optimal control
2015-06-22
– 2019-11-01Rhythm
Especially for generative music
2014-11-03
– 2019-10-23Delays and reverbs for audio processing
…ing …ing …ing
2015-11-11
– 2019-10-22State filtering parameters
Tracking things that don’t move
2017-09-15
– 2019-10-01Correlograms
Also covariances
2018-08-08
– 2019-09-22Defining dynamics via Gaussian processes
2019-09-18Signal sampling
Discrete representation of continuous signals and converse
2017-05-30
– 2019-03-08Decaying sinusoid dictionaries
2019-01-07Sparse 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
– 2018-01-05State filtering for hidden Markov models
Kalman and friends
2015-06-22
– 2017-07-06State space reconstruction
2014-10-13
– 2016-08-02Dynamical systems
2016-04-26
– 2016-07-27