How do science

Soft methodology of science 2012-01-13 – 2021-09-18

Reproducible research Open notebooks etc 2016-06-07 – 2021-09-16

Software engineering for scientists 2016-06-07 – 2021-09-16

Meta learning Few-shot learning, learning fast weights, learning to learn 2021-09-16

Machine learning for partial differential equations 2017-05-15 – 2021-09-07

Metis and .*-rationality High modernism, cargo culting, spontaneous order, legibility, the Great Society, technocracy, and local knowledge 2017-07-24 – 2021-09-06

Research discovery Has someone answered that question you have not worked out how to ask yet? 2019-01-22 – 2021-09-02

Scientific community Descriptive and normative 2021-08-24

Causal inference in highly parameterized ML 2020-09-18 – 2021-08-17

External validity Transfer learning, dataset shift, learning under covariate shift, transferable learning, domain adaptation etc 2020-10-17 – 2021-08-16

Convolutional stochastic processes Moving averages of noise 2021-03-01 – 2021-08-16

Tests, statistical Maybe also design of experiments while we are here? 2014-08-23 – 2021-08-04

Sequential experiments Especially multiple sequential experiments 2021-08-04

Digital scientific workbooks Literate coding for reality 2014-11-17 – 2021-07-27

Publication bias Replication crises, P-values, bitching about journals, other debilities of contemporary science at large 2016-08-30 – 2021-07-22

Science History, sociology and philosophy thereof 2017-07-08 – 2021-07-21

Blogdown Plus other RMarkdown-derived scholarly blogging systems 2020-08-26 – 2021-07-08

Academic blogging workflow Minimising the friction of advertising my thoughts in order to maximise the chance each thought gets advertised. Not covered: maximising quality of thoughts. 2020-05-22 – 2021-06-30

Dunning-Kruger theory of mind On anthropomorphising humans 2020-06-18 – 2021-06-25

Causality via potential outcomes Neyman-Rubin, counterfactuals, instrumental variables and related tricks 2016-10-26 – 2021-06-21

Phylogeny 2016-10-06 – 2021-06-14

Causal inference on DAGs Confounding! This scientist performed miracle graph surgery during an intervention and you won’t believe what happened next 2016-10-26 – 2021-05-19

Filter bubbles, fact checking and kompromat Polarization and fragmentation on the basis of browser cookies 2017-02-12 – 2021-04-25

Free will A matter about which I voluntarily admit I don’t care, but am compelled to have something to link to when eliding 2012-03-16 – 2021-04-23

Inference without KL divergence 2019-10-03 – 2021-04-23

Differentiable model selection Differentiable hyperparameter search, and architecture search, and optimisation optimisation by optimisation and so on 2020-09-25 – 2021-04-13

Machine learning for physical sciences Turbulent mixing at the boundary between two disciplines with differing inertia and viscosity 2017-05-15 – 2021-04-09

Scientific writing In which style tips are given for the projection of status through nominal phrases and passive voice 2014-12-31 – 2021-03-30

Science; Sociology and institution design for Scientist, falsify thyself 2020-05-17 – 2021-03-30

BibLaTeX Also BibTeX if you must 2020-09-29 – 2021-03-18

Probabilistic programming Programming with probability distributions for, e.g. Bayesian inference 2019-10-02 – 2021-03-10

knitr/RMarkdown 2020-02-02 – 2021-03-03

Learning on manifolds Finding the lowest bit of a krazy straw, from the inside 2011-10-21 – 2021-03-03

Convolutional Gaussian processes 2021-03-01

Stochastic processes on manifolds 2021-03-01

Hyperparameter optimization in ML Replacing a hyperparameter problem with a hyperhyperparameter problem which feels like progress I guess 2020-09-25 – 2021-03-01

Causal inference in the continuous limit 2021-02-17

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

Crowd-sourced science 2015-08-10 – 2020-11-24

Experiment tracking for computation science 2020-10-23 – 2020-11-06

Stan The flagship Bayesian workhorse 2020-10-19

Automatic design of experiments Minesweeper++ 2017-04-11 – 2020-10-13

AutoML 2017-07-17 – 2020-10-02

Research data sharing for science 2017-05-31 – 2020-09-23

Causal graphical model reading group 2020 An introduction to conditional independence DAGs and their use for causal inference. 2020-08-30 – 2020-09-03

Causal Bayesian networks Staged tree models, probability trees …Causlan Bayesian networks 2020-11-01 – 2020-09-01

Bushfire models 2020-09-07 – 2020-08-19

Citation management On PDFcocking 2014-09-08 – 2020-07-14

Knowledge geometry 2012-05-23 – 2020-05-22

Academic writing workflow Cranking the paper mill in the 21st century 2014-10-04 – 2020-05-18

Learning with conservation laws, invariances and symmetries 2020-04-11 – 2020-05-01

Academic publishing 2015-07-07 – 2020-04-16

Mechanism design for reputation systems Karma, credit scores, pagerank… 2014-08-05 – 2020-03-02

Selling uncertainty On the marginal price of ignorance 2016-05-25 – 2020-02-18

Anthropic principles Controlling for sampling bias in lived human experience 2020-02-15

R Shiny Statistics through the internet 2020-02-11

Bayes for beginners 2016-05-30 – 2020-01-30

Frequentist consistency of Bayesian methods TFW two flawed methods for understanding the world agree with at least each other 2016-04-12 – 2019-10-19

M-open, M-complete, M-closed 2016-05-30 – 2019-10-18

Betting and prediction markets Market design for good guesses 2017-08-12 – 2019-10-07

Social psychology Which of those NPR-friendly studies actually replicated? 2017-02-20 – 2019-10-03

First aid If you are checking this webpage while your colleague bleeds out, you are doing it wrong 2019-02-12

Multiple testing 2015-04-22 – 2018-11-05

Hamiltonian and Langevin Monte Carlo Physics might be on to something 2018-07-31 – 2018-07-12

Feature engineering for research and science 2017-05-31 – 2018-04-27

This is a simulation 2017-04-04

Pop social psychology 2015-03-31 – 2017-03-28

Hidden variable formalisms in quantum mechanics 2015-11-28

Science for policy 2011-08-07 – 2014-11-26