# approximation

Smooth transforms of Gaussian noise
Delta method, error propagation, unscented transform, Taylor expansion, in finite and inifinite dimensional spaces
2014-11-25
– 2022-05-12Expectation propagation
Generalized moment matching
2015-10-26
– 2022-05-04Generalized Bayesian Computation
2019-10-03
– 2022-04-28Inference without KL divergence
2019-10-03
– 2022-04-28SLAM
Simultaneous Location and Mapping
2014-11-25
– 2022-04-28Vecchia factoring of GP likelihoods
Ignore some conditioning in the dependencies and attain a sparse cholesky factor for the precision matrix
2022-04-27Basis-functions in Gaussian process regression
a.k.a Fixed Rank Kriging, basis function regression, weight space, spatial random effects
2022-02-22
– 2022-04-21Particle 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
– 2022-04-08Belief propagation
2014-11-25
– 2022-03-31Gaussian belief propagation
Least squares at maximal elaboration
2014-11-25
– 2022-03-28Generative flow
2022-03-07Message-passing algorithms in graphical models
Cleaving reality at the joint, then summing it at the marginal
2014-11-25
– 2022-02-17Variational inference
On fitting something not too far from a pretty good model that is not too hard
2016-03-22
– 2022-02-10Recommender systems
2020-11-30
– 2022-02-04Reparameterization tricks in inference
Pathwise gradient estimation, nNormalizing flows, invertible density models, inference by measure transport, low-dimensional coupling…
2018-04-04
– 2021-12-21Gaussian Processes as stochastic differential equations
Imposing time on things
2019-09-18
– 2021-11-25Neural diffusion models
2021-11-11
– 2021-11-11Deep generative models
2020-12-10
– 2021-11-11Learning on tabular data
2020-11-30
– 2021-06-21Optimal transport metrics
Wasserstein distances, Monge-Kantorovich metrics, Earthmover distances
2019-05-30
– 2021-06-08Energy based models
Inference with kinda-tractable un-normalized densities
2021-06-07Stein’s method
2021-03-12
– 2021-06-01Randomized low dimensional projections
2021-03-12
– 2021-05-24Limit Theorems
Asymptotic distributions of random processes
2014-11-25
– 2021-05-17Probability divergences
Metrics, contrasts and divergences and other ways of quantifying how similar are two randomnesses
2014-11-25
– 2021-05-12Generically approximating probability distributions
2021-03-12
– 2021-03-22Measure concentration inequalities
On being 80% sure I am only 20% wrong
2014-11-25
– 2021-03-04ELBO
Evidence lower bound, variational free energy etc
2020-10-02
– 2020-10-28Efficient factoring of GP likelihoods
2020-10-16
– 2020-10-26Data summarization
On maps drawn at smaller than 1:1 scale
2019-01-14
– 2020-09-18Variational autoencoders
2019-11-04
– 2020-09-10Variational inference
On fitting the best model one can be bothered to
2016-03-22
– 2020-05-24Likelihood free inference
2020-04-22The interpretation of densities as intensities and vice versa
Point process of observations ↔ observation of a point process
2016-09-13
– 2019-09-23Nearly sufficient statistics
How about “Sufficient sufficiency”? — is that taken?
2018-03-13
– 2019-01-14Metric entropy
2017-02-13Statistical learning theory
Eventually including structural risk minimisation, risk bounds, hopefully-uniform convergence rates, VC-dimension, generalisation-and-stability framings etc
2016-07-06
– 2016-08-16