# sdes

System identification in continuous time
Learning in continuous ODEs, SDEs and CDEs
2016-08-01
– 2023-11-30Machine learning for partial differential equations
2017-05-15
– 2023-11-17Feedback 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
– 2023-10-19Gradient flows
infinitesimal optimization
2020-01-30
– 2023-09-28Probabilistic numerics
2023-07-13
– 2023-09-25Machine learning for climate systems
2020-04-02
– 2023-09-25Potential theory in probability
Something about harmonic functions or whatever
2020-02-12
– 2023-08-24Materials informatics
Machine learning in condensed matter physics, chemistry and materials science
2023-08-01
– 2023-08-08Rough path theory and signature methods
2021-04-02
– 2023-06-29Neural learning dynamical systems
2018-08-13
– 2023-05-23Gradient descent, first-order, stochastic
a.k.a. SGD, as seen in deep learning
2020-01-30
– 2023-05-19Transforms 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
– 2022-12-07Deep learning as a dynamical system
2018-08-13
– 2022-10-30Neural tangent kernel
2020-12-09
– 2022-10-14Neural learning for spatiotemporal systems
2020-09-16
– 2022-07-28Overparameterization in large models
Improper learning, benign overfitting, double descent
2018-04-04
– 2022-05-27Stochastic partial differential equations
SDEs taking values in some function space
2021-01-27
– 2022-05-25(Discrete-measure)-valued stochastic processes
2019-10-10
– 2022-05-04Measure-valued stochastic processes
Moving masses
2020-10-16
– 2022-05-03Divisible, decomposable and stable distributions
Ways of slicing randomness
2017-06-15
– 2022-04-18Measure-valued random variates
Including completely random measures and many generalizations
2020-10-16
– 2022-03-30Feedback system identification, linear
2016-07-27
– 2022-01-21Gradient descent, Newton-like, stochastic
2020-01-23
– 2021-12-09Stochastic calculus
Itô and friends
2019-09-19
– 2021-08-31Contagion processes and their statistics
2016-08-30
– 2021-07-15Media virality
Strategic modelling for content creators
2016-08-30
– 2021-07-15Backward stochastic differential equations
2019-09-19
– 2021-06-22Stochastic differential equations
2019-09-19
– 2021-06-22Transforms of random variates
2020-06-04
– 2021-05-14Stochastic Taylor expansion
Polynomial approximations of small randomnesses, Itô’s lemma
2020-10-15
– 2021-05-14Infinite width limits of neural networks
2020-12-09
– 2021-05-11Path integral formulations of SDEs
Feynman path integrals, esp for stochastic processes
2021-04-19Chaos expansions
Polynomial chaos, generalized polynomial chaos, arbitrary chaos etc
2020-05-21
– 2021-02-15Malliavin calculus
2020-05-23
– 2020-05-25Lévy stochastic differential equations
2020-05-23Epidemics
2020-03-10
– 2020-04-03Infinitesimal generators
Generators of the transition semi-group, connection to Kolmogorov forward equations
2017-05-29
– 2020-02-05Cherchez la martingale
Stuff about probability and orthogonality
2019-11-25
– 2019-11-30Sparse stochastic processes identification and sampling
Discrete sample representation of sparse continuous stochastic processes
2018-11-22
– 2018-10-29Dynamical systems
2016-04-26
– 2016-07-27