dynamical_systems

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

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

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

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

Potential theory in probability Something about harmonic functions or whatever 2020-02-12 – 2023-08-24

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

Materials informatics Machine learning in condensed matter physics, chemistry and materials science 2023-08-01 – 2023-08-08

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

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

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

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

Statistical mechanics of statistics 2016-12-01 – 2023-06-02

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

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

Neural implicit representations Neural nets as coordinate mappings 2021-01-21 – 2023-04-26

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

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

Symbolic regression 2023-03-14

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

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

The edge of chaos Computation, evolution, competition and other past-times of faculty 2016-12-01 – 2022-10-30

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

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

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

State space reconstruction 2014-10-13 – 2022-08-30

Factorial hidden Markov models 2022-08-29

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

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

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

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

Divisible, decomposable and stable distributions Ways of slicing randomness 2017-06-15 – 2022-04-18

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

Reservoir Computing 2022-03-28

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

OODA loops 2021-05-01 – 2022-02-28

Stability in dynamical systems Lyapunov exponents and ilk 2019-05-21 – 2022-02-22

Ergodicity and mixing Things that probably happen eventually on average 2011-10-17 – 2022-02-13

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

Running neural nets backwards 2022-01-29

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

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

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

Networks and graphs, theory thereof 2014-11-24 – 2021-10-20

Random neural networks 2017-02-17 – 2021-10-12

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

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

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

Path integral formulations of SDEs Feynman path integrals, esp for stochastic processes 2021-04-19

Prediction processes Some kind of weird time series formalism 2021-04-09

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

Matrix measure concentration inequalities and bounds 2014-11-25 – 2021-03-08

Measure concentration inequalities The fancy name for probability inequalities 2014-11-25 – 2021-03-04

Random fields as stochastic differential equations Precision vs covariance, fight! 2020-10-12 – 2021-03-01

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

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

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

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

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

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

Lévy stochastic differential equations 2020-05-23

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

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

Infinitesimal generators Generators of the transition semi-group, connection to Kolmogorov forward equations 2017-05-29 – 2020-02-05

Convergence of random variables 2019-12-03

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

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

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

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

Defining dynamics via Gaussian processes 2019-09-18

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

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