# stochastic_processes

Transforms of RVs
2020-06-04
– 2021-05-14
Stochastic Taylor expansion
Polynomial approximations of small randomnesses
2020-10-15
– 2021-05-14
Stochastic differential equations
Itô and friends
2019-09-19
– 2021-05-13
Deep Gaussian process regression
2021-05-13
Infinite width limits of neural networks
2020-12-09
– 2021-05-11
Spectral factorization
2021-05-05
– 2021-05-07
Wiener-Hopf method
Righteous hack for certain integral equations
2021-05-05
Path continuity of stochastic processes
2020-02-26
– 2021-04-19
Path integral formulations of stochastic processes
Yes, Feynman integrals
2021-04-19
Gaussian process regression
And classification. And extensions.
2019-12-03
– 2021-04-13
Signatures of rough paths
Discrete representation of continuous signals and converse
2021-04-02
Kernel zoo
2019-09-16
– 2021-03-30
Neural nets with implicit layers
Also, declarative networks
2020-12-08
– 2021-03-15
Neural nets with basis decomposition layers
2021-03-09
Stochastic processes which represent measures over the reals
2020-10-16
– 2021-03-08
Convolutional subordinator processes
2021-03-08
Matrix measure concentration inequalities and bounds
2014-11-25
– 2021-03-08
Measure concentration inequalities
On being 80% sure you are only 20% wrong
2014-11-25
– 2021-03-04
Combining kernels
2019-09-16
– 2021-03-01
Convolutional Gaussian processes
2021-03-01
Random fields as stochastic differential equations
On ordering space in time
2020-10-12
– 2021-03-01
Convolutional stochastic processes
2021-03-01
Covariance functions
Variograms, Mercer kernels, positive definite operators, spare reproducing kernels for that Hilbert space I bought on eBay real cheap
2019-09-16
– 2021-03-01
Multi-output Gaussian process regression
2020-12-02
– 2021-02-23
Causal inference in the continuous limit
2021-02-17
Chaos expansions
Polynomial chaos, generalized polynomial chaos, arbitrary chaos etc
2020-05-21
– 2021-02-15
Stochastic partial differential equations
2021-01-27
Kernel warping
2019-09-16
– 2021-01-21
Miscellaneous nonstationary kernels
2019-09-16
– 2021-01-21
Statistical mechanics of statistics
2016-12-01
– 2021-01-06
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
Wiener-Khintchine representation
Now with bonus Bochner!
2019-05-08
– 2021-01-03
Nonparametrically learning dynamical systems
2018-08-13
– 2020-12-08
Multi-output Gaussian process regression
2020-12-07
Probabilistic spectral analysis
2019-11-13
– 2020-11-25
Hidden Markov Model inference for Gaussian Process regression
2019-09-18
– 2020-11-25
Bandit problems
Also reinforcement learning and stochastic control
2014-11-27
– 2020-10-16
Gamma processes
2019-10-14
– 2020-10-13
Subordinators
Non-decreasing Lévy processes with weird branding
2019-10-14
– 2020-10-08
Uncertainty quantification
2016-12-26
– 2020-10-06
Non-Gaussian Bayesian functional regression
2019-10-10
– 2020-09-16
Gaussian process quantile regression
2020-09-16
Statistics of spatio-temporal processes
2020-09-11
– 2020-09-11
Lévy processes
2017-05-29
– 2020-07-25
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
Forecasting
Haruspicy 2.0
2015-06-16
– 2020-05-21
Limit Theorems
Asymptotic distributions of random processes
2014-11-25
– 2020-05-06
Epidemics
2020-03-10
– 2020-04-03
Deep learning as a dynamical system
2018-08-13
– 2020-04-02
Nonparametrically learning spatiotemporal systems
2020-09-16
– 2020-04-02
Potential theory in probability
Something about harmonic functions or whatever
2020-02-12
Infinitesimal generators
Generators of the transition semi-group, connection to Kolmogorov forward equations
2017-05-29
– 2020-02-05
Poisson processes
2019-10-14
– 2020-01-29
Divisibility, decomposability, stability
Ways of slicing randomness
2017-06-15
– 2020-01-28
Markov bridge processes
2019-10-15
– 2020-01-20
Gaussian processes
2016-08-07
– 2019-12-03
Convergence of random variables
2019-12-03
(Discrete-measure)-valued stochastic processes
2019-10-10
Statistical learning theory for time series
2016-11-03
– 2019-10-01
Wiener theorem
Now with bonus Bochner!
2019-05-08
Sparse stochastic processes and sampling
Discrete sample representation of sparse continuous stochastic processes
2018-11-22
– 2018-10-29
Pattern formation
2014-12-23
– 2018-10-09
Stochastic processes and fields
Probabilistic structures over index sets and state spaces
2014-08-05
– 2017-06-15
Random neural networks
2017-02-17
– 2017-02-19
Fractional Brownian motion
2017-02-18
Contagion processes and their statistics
2016-08-30
– 2016-10-28
Maximum processes
2016-07-14
High frequency time series estimation
2016-06-12
– 2015-12-02