# networks

Designing social movements
Minimum viable utopia
2021-05-01
– 2021-05-14
Social norms
2019-10-07
– 2021-05-10
Queerness
2021-05-06
Diversity, oddness and multiculturalism in humans
On clone wars
2020-05-27
– 2021-05-03
Filter bubbles, fact checking and kompromat
Polarization and fragmentation on on the basis of browser cookies
2017-02-12
– 2021-04-25
Modern conspiracy mania
You are only reading this because the Deep State wants you to
2020-08-16
– 2021-04-25
Science; Sociology and institution design for
Scientist, falsify thyself
2020-05-17
– 2021-03-30
Diagramming and visualising graphical models
My need for this is conditionally dependent upon my deadline, given the subject matter
2018-03-29
– 2021-03-15
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 dynamics, opinion dynamics etc
2020-01-30
– 2021-02-27
Journalism, normative
2020-01-26
– 2021-02-19
Causal inference in the continuous limit
2021-02-17
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
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
Project management
With special attention to
2021-03-23
– 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
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
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