# nonparametric

Precision matrix estimation
Especially Gaussain
2014-11-16
– 2022-10-04The interpretation of RV densities as point process intensities and vice versa
Point process of observations ↔ observation of a point process
2016-09-13
– 2022-09-24Ensemble Kalman methods for training neural networks
Data assimilation for network weights
2022-09-20Gaussian process regression
And classification. And extensions.
2019-12-03
– 2022-09-20Neural process regression
2019-12-03
– 2022-09-20Learning Gamelan
2016-04-05
– 2022-08-05Gaussian process regression software
And classification.
2019-12-03
– 2022-07-29Simulating Gaussian processes on a lattice
2022-03-17
– 2022-07-26(Discrete-measure)-valued stochastic processes
2019-10-10
– 2022-05-04Generalized Bayesian Computation
2019-10-03
– 2022-04-28Bayesian nonparametric statistics
Updating more dimensions than datapoints
2016-05-30
– 2022-04-07Probabilistic neural nets
Bayesian and other probabilistic inference in overparameterized ML
2017-01-11
– 2022-04-07Measure-valued random variates
Including completely random measures and many generalizations
2020-10-16
– 2022-03-30Simulating Gaussian processes
2022-03-17Sparse coding
Wavelets, matching pursuit, overcomplete dictionaries…
2014-11-17
– 2022-03-07Survival analysis and reliability
Hazard rates, proportional hazard regression, life testing, mean time to failure
2019-03-12
– 2022-03-07Self-supervised learning
I just wanna be meeeeee / with high probabilityyy ♬♪
2022-03-04Neural nets with basis decomposition layers
2021-03-09
– 2022-02-01Karhunen-Loève expansions
2019-09-16
– 2022-02-01Bootstrap
Shuffling reality to produce your data
2014-11-26
– 2022-01-27Reparameterization tricks in inference
Pathwise gradient estimation, nNormalizing flows, invertible density models, inference by measure transport, low-dimensional coupling…
2018-04-04
– 2021-12-21t-processes
2021-11-10
– 2021-11-24Polynomial bases
2021-01-29
– 2021-10-06Gaussian processes
2016-08-07
– 2021-06-23Random-forest-like methods
A selection of randomly stopped clocks is never far from wrong.
2015-09-23
– 2021-06-17Functional regression
2016-01-05
– 2020-05-28Empirical estimation of information
Informing yourself from your data how informative your data was
2011-04-19
– 2020-04-28Mixture models for density estimation
2016-03-29
– 2020-04-24Kernel approximation
2016-07-27
– 2020-03-06Bias reduction
Estimating the bias of an estimator so as to subtract it off again
2020-02-26(Reproducing) kernel tricks
2014-08-18
– 2020-01-20Discrete time Fourier and related transforms
Also, chirplets, z-transforms, chromatic derivatives…
2019-10-17
– 2019-10-17Density estimation
Especially non- or semiparametrically
2016-06-06
– 2019-10-16Covariance matrix estimation
Esp Gaussian
2014-11-16
– 2019-09-21Wacky regression
2015-09-23
– 2019-05-02Inner product spaces
The most highly developed theory of squaring things
2019-01-01
– 2019-02-11Normed spaces
2019-01-01
– 2019-01-04Integral probability metrics
2016-08-21
– 2017-10-31Kernel density estimators
2016-03-05
– 2016-08-18Function approximation and interpolation
2016-06-09Deconvolution
2015-04-19
– 2016-04-11