# probability

High dimensional statistics
2015-03-12
– 2021-10-28
Anthropic principles
Convenience-sampling lived human experience
2020-02-15
– 2021-10-28
Random graphical models
Causality in amongst confusion
2021-10-26
– 2021-10-28
Causal inference in highly parameterized ML
2020-09-18
– 2021-10-27
External validity
Transfer learning, dataset shift, learning under covariate shift, transferable learning, domain adaptation etc
2020-10-17
– 2021-10-26
Fun with rotational symmetries
2021-01-29
– 2021-10-14
Neural music synthesis
2016-01-15
– 2021-10-14
Missing data
Imputation, estimation despite etc
2021-10-07
Mind as statistical learner
2020-06-23
– 2021-10-05
The Gaussian distribution
The probability distribution that you give up and use in the end
2016-06-27
– 2021-10-03
Science for policy
Using evidence and reason to govern ourselves
2011-08-07
– 2021-09-22
Approximate Bayesian Computation
Posterior updates without likelihood
2020-08-25
– 2021-09-20
Heavy tails
Weird things about rare massive events
2020-01-13
– 2021-09-18
Diagramming and visualising graphical models and neural networks
My need for this is conditionally dependent upon my deadline, given the subject matter
2018-03-29
– 2021-09-06
Monte Carlo methods
2014-11-16
– 2021-09-02
Path smoothness properties of stochastic processes
Continuity, differentiability and other smoothness properties
2020-02-26
– 2021-09-02
Stochastic calculus
Itô and friends
2019-09-19
– 2021-08-31
Inverse problems
2016-03-30
– 2021-08-23
Risk neutral measure
2021-10-15
– 2021-08-08
Risk neutral measure
2021-10-15
– 2021-08-08
Trading, hedging and portfolios in practice
2017-05-09
– 2021-08-08
Cascade models
a.k.a. cluster distributions, Galton-Watson models
2019-10-11
– 2021-08-04
Laplace approximations in inference
Posterior updates without likelihood
2021-07-28
Risk perception and communication
2011-04-14
– 2021-07-27
Recommender systems
2020-11-30
– 2021-07-19
Contagion processes and their statistics
2016-08-30
– 2021-07-15
Media virality
Strategic modelling for content creators
2016-08-30
– 2021-07-15
Learning summary statistics
2020-04-22
– 2021-07-15
Graph sampling
Estimating functionals of graphs
2020-02-15
– 2021-07-06
Extreme value theory
On the decay of awfulness with oftenness
2020-01-13
– 2021-06-30
Predictive coding
Fancy analogy for brains
2011-11-27
– 2021-06-24
Algebraic probability
If you liked it then you prob’ly put a ring on it
2017-06-15
– 2021-06-24
Stochastic partial differential equations
2021-01-27
– 2021-06-24
Stochastic differential equations
2019-09-19
– 2021-06-22
Causality via potential outcomes
Neyman-Rubin, counterfactuals, instrumental variables and related tricks
2016-10-26
– 2021-06-21
Learning on tabular data
2020-11-30
– 2021-06-21
Random rotations
2021-05-18
– 2021-06-08
Optimal transport metrics
Wasserstein distances, Monge-Kantorovich metrics, Earthmover distances
2019-05-30
– 2021-06-08
Deep generative models
2020-12-10
– 2021-06-08
Energy based models
Inference with kinda-tractable un-normalized densities
2021-06-07
Stein’s method
2021-03-12
– 2021-06-01
Isotropic random vectors
2011-08-10
– 2021-05-24
Randomized low dimensional projections
2021-03-12
– 2021-05-24
Gaussian Process regression via state filtering
Imposing time on things
2019-09-18
– 2021-05-21
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
Limit Theorems
Asymptotic distributions of random processes
2014-11-25
– 2021-05-17
Transforms of RVs
2020-06-04
– 2021-05-14
Stochastic Taylor expansion
Polynomial approximations of small randomnesses
2020-10-15
– 2021-05-14
Cross validation
2016-09-05
– 2021-05-13
Probability divergences
Metrics, contrasts and divergences and other ways of quantifying how similar are two randomnesses
2014-11-25
– 2021-05-12
Spectral factorization
2021-05-05
– 2021-05-07
Wiener-Hopf method
Righteous hack for certain integral equations
2021-05-05
Inference without KL divergence
2019-10-03
– 2021-04-23
Path integral formulations
Feynman path integrals, esp for stochastic processes
2021-04-19
Prediction processes
Some kind of weird time series formalism
2021-04-09
Generically approximating probability distributions
2021-03-12
– 2021-03-22
Log concave distributions
associated tools
2017-08-28
– 2021-03-11
Markov Chain Monte Carlo methods
2017-08-28
– 2021-03-11
Reparameterization tricks in inference
Normalizing flows, invertible density models, inference by measure transport, low-dimensional coupling…
2018-04-04
– 2021-03-08
Stochastic processes which represent measures over the reals
2020-10-16
– 2021-03-08
Matrix measure concentration inequalities and bounds
2014-11-25
– 2021-03-08
Measure concentration inequalities
On being 80% sure I am only 20% wrong
2014-11-25
– 2021-03-04
Random fields as stochastic differential equations
2020-10-12
– 2021-03-01
Frames and Riesz bases
Generalisations of orthogonal bases
2017-06-12
– 2021-02-24
Causal inference in the continuous limit
2021-02-17
Stability in linear dynamical systems
This Bodes well
2019-07-19
– 2021-02-16
Chaos expansions
Polynomial chaos, generalized polynomial chaos, arbitrary chaos etc
2020-05-21
– 2021-02-15
Feynman-Kac formulae
2021-01-27
Generative adversarial networks
2016-10-07
– 2020-12-14
Random embeddings and hashing
2016-12-05
– 2020-12-01
Randomised regression
2017-01-13
– 2020-12-01
Variational inference by message-passing in graphical models
2014-11-25
– 2020-11-25
Probabilistic spectral analysis
2019-11-13
– 2020-11-25
Weighted data in statistics
2020-11-04
– 2020-11-06
Markov Chain Monte Carlo methods
2020-06-28
– 2020-10-28
ELBO
Evidence lower bound, variational free energy etc
2020-10-02
– 2020-10-28
Efficient factoring of GP likelihoods
2020-10-16
– 2020-10-26
Differentiating through the Gamma
2020-06-12
– 2020-10-15
Gamma processes
2019-10-14
– 2020-10-13
Inverse problems for complex models
a.k.a. Bayesian calibration, model uncertainty
2020-10-13
Subordinators
Non-decreasing Lévy processes with weird branding
2019-10-14
– 2020-10-08
Sparse model selection
2016-09-05
– 2020-10-02
Monte Carlo gradient estimation
2020-09-30
Monte Carlo optimisation
2020-09-30
Splitting simulation
2017-05-29
– 2020-09-28
Quantitative risk measurement
Mathematics of actuarial and financial disaster
2015-04-30
– 2020-09-22
Data summarization
On maps drawn at smaller than 1:1 scale
2019-01-14
– 2020-09-18
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
Variational autoencoders
2019-11-04
– 2020-09-10
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
Online learning
2018-09-30
– 2020-08-26
Lévy processes
2017-05-29
– 2020-07-25
(Approximate) matrix factorisation
2014-08-05
– 2020-07-03
Variational inference
On fitting the best model one can be bothered to
2016-03-22
– 2020-05-24
Directed graphical models
2017-09-20
– 2020-05-13
Learning with conservation laws, invariances and symmetries
2020-04-11
– 2020-05-01
Adaptive Markov Chain Monte Carlo samplers
2020-04-28
– 2020-04-30
Tuning an MCMC sampler
2020-04-30
– 2020-04-30
Statistical projectivity
2020-04-26
The cross entropy method
2020-04-24
Mixture models for density estimation
2016-03-29
– 2020-04-24
Likelihood free inference
2020-04-22
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
Particle filters
incorporating Interacting Particle Systems, Sequential Monte Carlo and a profusion of other simultaneous-discovery names
2014-07-25
– 2020-04-08
Queueing
The mathematical field whose major result is enraging you about call centres
2015-06-03
– 2020-04-06
Order statistics
2019-02-21
– 2020-03-17
Restricted isometry properties
Plus incoherence, irrepresentability, and other uncertainty bounds for a sparse world, and maybe frame theory, what’s that now?
2017-06-12
– 2020-03-09
Potential theory in probability
Something about harmonic functions or whatever
2020-02-12
Random change of time
Stochastic processes derived by varying the rate of time’s passage, which is more convenient than I imagined
2015-08-05
– 2020-02-10
Branching processes
2014-08-18
– 2020-02-07
Survival analysis and reliability
Hazard rates, proportional hazard regression, life testing, mean time to failure
2019-03-12
– 2020-02-05
Infinitesimal generators
Generators of the transition semi-group, connection to Kolmogorov forward equations
2017-05-29
– 2020-02-05
Conditional expectation and probability
2020-02-04
Poisson processes
2019-10-14
– 2020-01-29
Divisibility, decomposability, stability
Ways of slicing randomness
2017-06-15
– 2020-01-28
Markov bridge processes
2019-10-15
– 2020-01-20
Hawkes processes
2019-12-22
Factor graphs
2019-12-16
Convergence of random variables
2019-12-03
Cherchez la martingale
Stuff about probability and orthogonality
2019-11-25
– 2019-11-30
Audio source separation
2019-11-04
– 2019-11-26
Time frequency analysis
Multiplying your exposure to uncertainty principles
2018-01-06
– 2019-11-26
Optimal control
2015-06-22
– 2019-11-01
Gaussian processes on lattices
2019-10-30
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
Sparse regression
2016-06-23
– 2019-10-24
Density estimation
Especially non- or semiparametrically
2016-06-06
– 2019-10-16
Non-negative matrix factorisation
2019-10-14
Zeros of random trigonometric polynomials
2019-05-20
– 2019-10-14
Exponential families
2016-04-19
– 2019-10-12
Generalized Galton-Watson processes
2014-12-28
– 2019-10-11
Random matrix theory
2014-11-09
– 2019-10-10
(Discrete-measure)-valued stochastic processes
2019-10-10
State filtering parameters
Tracking things that don’t move
2017-09-15
– 2019-10-01
Probabilistic graphical models over continuous index sets
2014-08-05
– 2019-09-25
The interpretation of densities as intensities and vice versa
Point process of observations ↔ observation of a point process
2016-09-13
– 2019-09-23
Defining dynamics via Gaussian processes
2019-09-18
Large sample theory
2015-02-15
– 2019-09-09
Hierarchical models
DAGs, multilevel models, random coefficient models, mixed effect models…
2015-06-07
– 2019-08-19
Probability
2011-07-29
– 2019-07-15
Fourier interpolation
2019-06-19
Stability in dynamical systems
Lyapunov exponents and ilk
2019-05-21
Nearly sufficient statistics
How about “Sufficient sufficiency”? — is that taken?
2018-03-13
– 2019-01-14
Variational state filtering
2018-03-19
– 2018-12-07
Anomaly detection
I don’t define what is normal, but I know it when I see it
2015-10-06
– 2018-10-22
Rare-event-conditional estimation
2017-05-29
– 2017-11-10
Gaussian Process simulation and circulant embeddings
I might shoehorn Whittle likelihoods in here too
2017-11-10
– 2017-11-10
Quantum probability
and quantum information, noncommutative probability
2016-10-16
– 2017-09-18
Probabilistic graphical models
2014-08-05
– 2017-09-11
Quantum-probabilistic graphical models
2017-08-07
Warping and registration problems
Matching up of bumps and wibbles in stretchy things
2016-08-17
– 2017-07-23
State filtering for hidden Markov models
Kalman and friends
2015-06-22
– 2017-07-06
Generating functions
Fancy counting
2017-06-19
Stochastic processes and fields
Probabilistic structures over index sets and state spaces
2014-08-05
– 2017-06-15
Compressed sensing / compressed sampling
The fanciest ways of counting zero
2014-08-18
– 2017-06-14
Marketing psychology
2017-04-27
– 2017-05-29
Uncertainty principles
2017-05-14
Fractional Brownian motion
2017-02-18
Metric entropy
2017-02-13
Special functions
2014-07-25
– 2016-12-21
The simplex
2016-10-25
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
Maximum likelihood inference
2015-02-15
– 2016-10-13
Penalised/regularised regression
2016-06-23
– 2016-09-15
Statistical 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
Randomised linear algebra
2016-08-16
Change of probability measure
2015-08-05
– 2016-08-16
Blind deconvolution
2015-03-01
– 2016-07-27
Kernel approximation
2016-07-27
Maximum processes
2016-07-14
Curved exponential families
2016-04-19
Expectation maximisation
2014-08-17
– 2016-04-17
Deconvolution
2015-04-19
– 2016-04-11
Indirect inference
2014-12-23
– 2015-12-15
Count time series models
2015-06-03
– 2015-12-09
Hidden variable formalisms in quantum mechanics
2015-11-28
Random number generation
2015-05-14
– 2015-10-13
Copula functions
2015-06-23
Elliptical distributions
2015-06-23
Sigma algebras, probability spaces, measure theory
The scaffolding of randomness
2015-06-20