Pytorch #torched 2018-05-04 – 2022-05-18
Smooth transforms of Gaussian noise Delta method, error propagation, unscented transform, Taylor expansion, in finite and inifinite dimensional spaces 2014-11-25 – 2022-05-12
SLAM Simultaneous Location and Mapping 2014-11-25 – 2022-04-28
Anomaly detection I don’t define what is abnormal, but I know it when I see it 2015-10-06 – 2022-04-21
Hierarchical models DAGs, multilevel models, random coefficient models, mixed effect models, structural equation models… 2015-06-07 – 2022-04-21
Saying “Bayes” is not enough Bayesians are usually not actually doing Bayesian reasoning well and even if we were, it would be insufficient to do science, or life 2016-05-30 – 2022-04-15
Particle filters incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names 2014-07-25 – 2022-04-10
Science communication On making people feel they are smart enough to teach themselves, or failing that, that they are smart enough to fund YOU to teach yourself 2021-06-02 – 2022-04-05
Predictive coding Does the model that our brains do bayesian variational prediction make any actual predictions about our brains? 2011-11-27 – 2022-04-04
Change points Looking for regime changes in stochastic processes. a.k.a. Switching state space models 2021-11-29 – 2022-04-01
Random binary vectors The class of distributions that cause you to reinvent Shannon information if you stare at them long enough 2017-02-20 – 2022-03-30
Causal inference on DAGs Confounding! This scientist performed a miracle graph surgery intervention and you won’t believe what happened next 2016-10-26 – 2022-03-08
Data dashboards and ML demos On assuring the client that you are doing something data-sciency because it looks like in the movies 2020-03-12 – 2022-03-07
Optimal transport inference I feel the earth mover under my feet, I feel the ψ tumbling down, I feel my heart start to trembling, Whenever you’re around my empirical density in minimal transport cost 2021-03-16 – 2022-02-22
Variational inference On fitting something not too far from a pretty good model that is not too hard 2016-03-22 – 2022-02-10
Bootstrap Shuffling reality to produce your data 2014-11-26 – 2022-01-27
Psychometrics Dimensionality reduction for souls 2017-10-31 – 2022-01-26
Reparameterization tricks in inference Pathwise gradient estimation, nNormalizing flows, invertible density models, inference by measure transport, low-dimensional coupling… 2018-04-04 – 2021-12-21
R The statistical programming language, not the letter 2011-08-07 – 2021-12-14
Pyro Approximate maximum in the density of probabilistic programming effort 2019-10-02 – 2021-11-25
(Geo)spatial data sets In which I complain about paying a nominal fee for giant rocket robots that scan the earth from space 2021-03-02 – 2021-10-13
Science for policy Using evidence and reason to govern ourselves 2011-08-07 – 2021-09-22
Heavy tails Weird things about rare massive events 2020-01-13 – 2021-09-18
Publication bias Replication crises, P-values, bitching about journals, other debilities of contemporary science at large 2016-08-30 – 2021-07-22
IDEs for R Friendly UIs for the almost-friendly statistical programming language 2011-08-07 – 2021-07-18
Media virality Strategic modelling for content creators 2016-08-30 – 2021-07-15
Tensorflow The framework to use for deep learning if you groupthink like Google 2016-07-11 – 2021-07-07
Graph sampling Estimating functionals of graphs 2020-02-15 – 2021-07-06
Probability divergences Metrics, contrasts and divergences and other ways of quantifying how similar are two randomnesses 2014-11-25 – 2021-05-12
Bayesians vs frequentists Just because we both get the same answer doesn’t mean neither of us is wrong 2014-11-25 – 2021-01-14
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
Data sets Questions for answers looking for questions 2015-06-26 – 2020-12-02
ELBO Evidence lower bound, variational free energy etc 2020-10-02 – 2020-10-28
Stan The flagship Bayesian workhorse 2020-10-19
Dimensionality reduction Wherein I teach myself, amongst other things, feature selection, how a sparse PCA works, and decide where to file multidimensional scaling 2015-03-22 – 2020-09-11
Learning of manifolds Also topological data analysis; other hip names to follow 2014-08-19 – 2020-06-23
Queueing The mathematical field whose major result is enraging you about call centres 2015-06-03 – 2020-04-06
Model averaging On keeping many incorrect hypotheses and using them all as one goodish one 2017-06-20 – 2020-03-22
Bias reduction Estimating the bias of an estimator so as to subtract it off again 2020-02-26
R Shiny Statistics through the internet 2020-02-11
Informations Entropies and other measures of surprise 2011-11-25 – 2019-09-10
Signal sampling Discrete representation of continuous signals and converse 2017-05-30 – 2019-03-08
Signal processing That which you study for 4 years in order to design trippy music visualisers 2015-03-18 – 2018-01-05