# algebra

Computational Fluid Dynamics
2021-01-27
– 2023-11-30Learning graphical models from time series
Also, causal discovery, structure discovery in time series
2017-09-20
– 2023-11-28Automatic differentiation
2016-07-27
– 2023-11-15Causal inference in highly parameterized ML
2020-09-18
– 2023-10-24Learning under distribution shift
Also transfer learning, covariate shift, transferable learning, domain adaptation, transportability etc
2020-10-17
– 2023-10-24Numerical PDE solvers
2016-03-01
– 2023-10-23Orthonormal and unitary matrices
Energy preserving operators, generalized rotations
2019-10-22
– 2023-09-19Differential geometry, geometric algebra etc
2014-11-27
– 2023-09-19Potential theory in probability
Something about harmonic functions or whatever
2020-02-12
– 2023-08-24Ablation studies and lesion studies
In order to understand it we must be able to break it
2016-10-26
– 2023-08-01Factor graphs
2019-12-16
– 2023-07-31Matrix calculus
2018-07-09
– 2023-07-24(Reproducing) kernel tricks
2014-08-18
– 2023-07-21The Gaussian distribution
The default probability distribution
2016-06-27
– 2023-07-19Hypothesis tests, statistical
2014-08-23
– 2023-07-18Gaussian process ensembles
Bayesian committee machines, product-of-experts
2023-07-12Matrix norms, divergences, metrics
2016-06-03
– 2023-05-29Belief propagation
2014-11-25
– 2023-05-17Canonical correlation
2014-08-23
– 2023-05-17Jax
Julia for python
2020-09-15
– 2023-05-12Distances between Gaussian distributions
Nearly equivalent to distances between symmetric positive definite matrices
2016-06-27
– 2023-05-03Covariance estimation
Esp Gaussian
2014-11-16
– 2023-04-26Optimal rotations
2021-05-18
– 2023-04-06Mathematica
2011-04-06
– 2023-04-05Tensor decompositions
2016-08-15
– 2023-02-21External validity
When does what I learn on one data set apply to another?
2020-10-17
– 2023-02-16The Matrix-Gaussian distribution
2022-08-19
– 2023-02-16Last-layer Bayes neural nets
Bayesian and other probabilistic inference in overparameterized ML
2017-01-11
– 2023-02-09Visualising probabilistic graphical models
Also related models, such as Neural nets
2018-03-29
– 2023-02-02Variational message-passing algorithms in graphical models
Cleaving reality at the joint, then summing it at the marginal
2014-11-25
– 2023-01-12Elliptical distributions
2015-06-23
– 2023-01-03Graph neural nets
2020-09-16
– 2022-12-19Adverse advice selection
2022-01-25
– 2022-11-15Interaction effects and subgroups are probably what we want to estimate
2022-01-25
– 2022-11-06Randomised linear algebra
2016-08-16
– 2022-10-22Neural tangent kernel
2020-12-09
– 2022-10-14Precision matrix estimation
Especially Gaussain
2014-11-16
– 2022-10-04Learning graphical models from data
Also, causal discovery, structure discovery
2017-09-20
– 2022-10-01Conditional expectation and probability
2020-02-04
– 2022-09-21Gaussian belief propagation
Least squares at maximal elaboration
2014-11-25
– 2022-09-01Elliptical belief propagation
Generalized least generalized squares
2022-08-22
– 2022-08-23Automatic differentiation in Julia
2016-07-27
– 2022-08-09Causal inference on DAGs
Confounding! This scientist performed a miracle graph surgery intervention and you won’t believe what happened next
2016-10-26
– 2022-08-06Instumental variables and two stage regression
Confounding! This scientist performed a miracle graph surgery intervention and you won’t believe what happened next
2016-10-26
– 2022-08-06Bayes linear regression and basis-functions in Gaussian process regression
a.k.a Fixed Rank Kriging, weight space GPs
2022-02-22
– 2022-07-27Partial differential equations
2021-01-27
– 2022-07-23Causal graphical model reading group 2022
Causal inference
2022-04-01
– 2022-04-29SLAM
Simultaneous Location and Mapping
2014-11-25
– 2022-04-28Vecchia factoring of GP likelihoods
Ignore some conditioning in the dependencies and attain a sparse cholesky factor for the precision matrix
2022-04-27Beta Processes
2019-10-14
– 2022-04-08Stationary Gamma processes
2019-10-14
– 2022-04-08Particle belief propagation
Graphical inference using empirical distribution estimates
2014-07-25
– 2022-04-08Particle Markov Chain Monte Carlo
Particle systems as MCMC proposals
2014-07-25
– 2022-04-08Partition-valued random variates
2022-04-01Multivariate Gamma distributions
2019-10-14
– 2022-03-14Fun with rotational symmetries
2021-01-29
– 2022-03-03Learning with conservation laws, invariances and symmetries
2020-04-11
– 2022-02-25Probabilistic graphical models
2014-08-05
– 2022-02-08Random graphical models
Causality in amongst confusion
2021-10-26
– 2022-02-07Matrix-valued random variates
2021-12-01
– 2022-01-06Causality via potential outcomes
Neyman-Rubin, counterfactuals, conditional treatment effects, and related tricks
2016-10-26
– 2021-12-10Random rotations
2021-05-18
– 2021-12-01Gaussian Processes as stochastic differential equations
Imposing time on things
2019-09-18
– 2021-11-25Spectral graph theory
Linear signals on graphs
2014-11-24
– 2021-10-27Neural music synthesis
2016-01-15
– 2021-10-14Fun with determinants
Especially Jacobian determinants
2011-04-06
– 2021-10-12Multilinear algebra
Outer products, tensors, einstein summation
2021-10-08Arpeggiate by numbers
Workaday automatic composition and sequencing
2015-01-07
– 2021-09-20Algebraic probability
If you liked it then you prob’ly put a ring on it
2017-06-15
– 2021-06-24Isotropic random vectors
2011-08-10
– 2021-05-24Randomized low dimensional projections
2021-03-12
– 2021-05-24Infinite width limits of neural networks
2020-12-09
– 2021-05-11Computational symbolic mathematics
Cheating at calculus exams
2016-10-13
– 2021-05-11Tensor regression
2020-11-19Efficient factoring of GP likelihoods
2020-10-16
– 2020-10-26GP inducing features
2020-10-16
– 2020-10-26GP inducing variables
2020-10-16
– 2020-10-26Localized Gaussian processes
2020-10-16
– 2020-10-26Independence, conditional, statistical
2016-04-21
– 2020-09-13Causal graphical model reading group 2020
An introduction to conditional independence DAGs and their use for causal inference.
2020-08-30
– 2020-09-03Causal Bayesian networks
Staged tree models, probability trees …Causalan Bayesian networks
2020-11-01
– 2020-09-01Mathematics of textiles
2019-10-14
– 2020-08-20MAPLE
An OK computer algebra system
2020-05-19Directed graphical models
2017-09-20
– 2020-05-13Analysis/resynthesis of audio
2016-01-15
– 2020-04-09Kernel approximation
2016-07-27
– 2020-03-06Audio source separation
2019-11-04
– 2019-11-26Tunings
2015-10-29
– 2019-11-18Undirected graphical models
2017-09-20
– 2019-10-28Random (element) matrix theory
2014-11-09
– 2019-10-10Probability
2011-07-29
– 2019-07-15Inner product spaces
The most highly developed theory of squaring things
2019-01-01
– 2019-02-11Normed spaces
2019-01-01
– 2019-01-04Linear algebra
If the thing is twice as big, the transformed version of the thing is also twice as big. {End}
2011-04-06
– 2018-08-07Musical metrics and manifolds
2014-09-26
– 2017-03-27Functional equations
Putting the funk in functions
2017-02-06
– 2017-02-19Category theory
2011-11-25
– 2016-04-18Expectation maximisation
2014-08-17
– 2016-04-17Coarse graining
2014-11-11
– 2015-12-02Sigma algebras, probability spaces, measure theory
The scaffolding of randomness
2015-06-20Algebra I would like to learn
2014-10-15
– 2014-11-22