networks

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

Red queen social signal dynamics Arms races in memetic selection on graphs is how I make my fashion choices 2018-12-18 – 2021-02-27

Memetics Taste and opinion dynamics 2020-01-30 – 2021-02-27

Social norms 2019-10-07 – 2021-02-25

Journalism, normative 2020-01-26 – 2021-02-19

Causal inference in the continuous limit 2021-02-17

Science; Sociology and institution design for Scientist, research thyself 2020-05-17 – 2021-01-06

Diagramming and visualising graphical models My need for this is conditionally dependent upon my deadline, given the subject matter 2018-03-29 – 2021-01-03

Diagramming and visualising graphical models My need for this is conditionally dependent upon my deadline, given the subject matter 2018-03-29 – 2021-01-03

Weaponised social media Trolls, bots, lulz, infowars and other moods of the modern networked ape 2019-10-21 – 2020-12-01

Recommender systems 2020-11-30

Variational inference by message-passing in graphical models 2014-11-25 – 2020-11-25

Graph neural nets 2020-09-16 – 2020-11-24

External validity Transfer learning, dataset shift, learning under covariate shift, transferable learning, domain adaptation etc 2020-10-17 – 2020-11-09

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 – 2020-11-04

Efficient factoring of GP likelihoods 2020-10-16 – 2020-10-26

The levels of simulacra 2018-12-18 – 2020-10-19

Graph computation 2014-12-17 – 2020-09-20

Causal inference in highly parameterized ML 2020-09-18

Applied string mangling Regexes, parsing, tokenising etc 2019-12-09 – 2020-09-14

Independence, conditional, statistical 2016-04-21 – 2020-09-13

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

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

Modern conspiracy mania You are only reading this because the Deep State wants you to 2020-08-16 – 2020-08-17

Dilemmas of collective action 2014-11-25 – 2020-08-01

Recommended workplace habits 2020-07-19

Designing less toxic social media 2020-07-12

(Approximate) matrix factorisation 2014-08-05 – 2020-07-03

Teamwork 2020-01-26 – 2020-07-02

Economics of insurgence 2015-02-02 – 2020-07-01

Research discovery Has someone answered that question you have not worked out how to ask yet? 2019-01-22 – 2020-06-26

Learning of manifolds Also topological data analysis; other hip names to follow 2014-08-19 – 2020-06-23

Economics on networks 2020-05-17 – 2020-06-16

Soft methodology of science 2012-01-13 – 2020-06-11

Science, history and philosophy thereof 2017-07-08 – 2020-06-05

Pluralistic ignorance We all believe that we all believe what we do not believe 2020-06-03

Inference on social graphs Heterogeneous media and controls 2019-09-22 – 2020-06-03

Natural gradient descent Climbing slower on the tricky bits 2019-07-18 – 2020-05-26

Incentive mechanism design Markets, cakes, karma, and games 2014-09-22 – 2020-05-24

But what can I do? The stuff to do to make a better society is so easy that it is embarrassing if you are not doing it 2020-02-06 – 2020-05-19

Directed graphical models 2017-09-20 – 2020-05-13

Contact tracing Reverse engineering social graphs for the control of contagions of pathogens, subversive ideology and other substances of interest to control 2020-03-21 – 2020-05-10

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

Statistical relational learning 2020-04-26 – 2020-04-27

Statistical projectivity 2020-04-26

Learning summary statistics 2020-04-22

Post stratification Making the optimal lemonade from the fruit life gave you 2020-04-22

Survey modelling Adjusting for the Lizardman constant 2019-08-29 – 2020-04-21

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

Learning graphical models from data What is independent of what? 2017-09-20 – 2020-04-11

Analysis/resynthesis of audio 2016-01-15 – 2020-04-09

Epidemics 2020-03-10 – 2020-04-03

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

Learnable indexes and hashes 2018-01-12 – 2020-02-18

Graph sampling 2020-02-15

Potential theory in probability Something about harmonic functions or whatever 2020-02-12

Conditional expectation and probability 2020-02-04

Recurrent neural networks 2016-06-16 – 2020-01-23

*-omics 2016-08-12 – 2020-01-22

Applied psephology 2016-07-12 – 2020-01-20

Information geometry 2011-10-21 – 2019-12-27

Factor graphs 2019-12-16

Filter bubbles, fact checking and kompromat The high price of cheap talk in the mass media 2017-02-12 – 2019-12-07

Audio source separation 2019-11-04 – 2019-11-26

Inference on graphical models Given what I know about what I know, what do I know? 2017-09-20 – 2019-10-28

Undirected graphical models 2017-09-20 – 2019-10-28

Non-negative matrix factorisation 2019-10-14

Probabilistic graphical models over continuous index sets 2014-08-05 – 2019-09-25

Hierarchical models DAGs, multilevel models, random coefficient models, mixed effect models… 2015-06-07 – 2019-08-19

Fourier interpolation 2019-06-19

Topology, applied to problems I know about 2015-01-23 – 2019-06-15

Networks and graphs, theory thereof 2014-11-24 – 2018-11-05

Probabilistic graphical models 2014-08-05 – 2017-09-11

Probabilistic graphical models 2014-08-05 – 2017-09-11

Quantum-probabilistic graphical models 2017-08-07

Marketing psychology 2017-04-27 – 2017-05-29

Standards hell Lock-in, QWERTY etc 2015-01-05 – 2017-05-08

Random neural networks 2017-02-17 – 2017-02-19

Contagion processes and their statistics 2016-08-30 – 2016-10-28

UNSW Stats reading group 2016 - Causal DAGs An introduction to conditional independence DAGs and their use for causal data. 2016-10-17 – 2016-10-21

Inference from disorder 2016-10-19

Clustering 2015-05-22 – 2016-06-07

Coarse graining 2014-11-11 – 2015-12-02

Sigma algebras, probability spaces, measure theory The scaffolding of randomness 2015-06-20

Dunbar’s number 2011-12-09