feature_construction

Simulation-based inference 2014-12-23 – 2023-11-23

Quantization 2016-03-29 – 2023-11-02

Non-negative matrix factorisation 2019-10-14 – 2023-10-26

Low-rank matrices 2014-08-05 – 2023-09-29

Matrix inverses 2014-08-05 – 2023-09-29

Nearly-low-rank Hermitian matrices a.k.a. perturbations of the identity, low-rank-plus-diagonal matrices 2014-08-05 – 2023-09-13

Approximate matrix factorisations and decompositions Sometimes even exact 2014-08-05 – 2023-08-23

Neural vector embeddings Hyperdimensional Computing, Vector Symbolic Architectures, Holographic Reduced Representations 2017-12-20 – 2023-06-13

Noise contrastive estimation Also “negative sampling”. 2020-04-22 – 2023-06-06

Matrix norms, divergences, metrics 2016-06-03 – 2023-05-29

Singular Value Decomposition The ML workhorse 2014-08-05 – 2023-05-23

Matrix square roots Whitening, preconditioning etc 2014-08-05 – 2023-05-13

Model order reduction 2015-03-22 – 2023-04-21

Deep sets invariant and equivariant functions 2022-11-24 – 2023-03-21

(Nearly-)Convex relation of nonconvex problems 2018-04-04 – 2023-03-17

Density ratio tricks 2022-12-06

Randomised linear algebra 2016-08-16 – 2022-10-22

Laplace approximations in inference Lightweight uncertainties, especially for heavy neural nets 2021-07-28 – 2022-09-06

Semantics Compressed representations of reality for syntactic agents; which might be what meaning means 2014-12-29 – 2022-08-28

Integrated Nested Laplace Approximation 2021-07-28 – 2022-07-26

Overparameterization in large models Improper learning, benign overfitting, double descent 2018-04-04 – 2022-05-27

Reservoir Computing 2022-03-28

Random neural networks 2017-02-17 – 2021-10-12

Approximate Bayesian Computation Posterior updates without likelihood 2020-08-25 – 2021-09-20

Learning summary statistics 2020-04-22 – 2021-07-15

Randomized low dimensional projections 2021-03-12 – 2021-05-24

Infinite width limits of neural networks 2020-12-09 – 2021-05-11

Random embeddings and hashing 2016-12-05 – 2020-12-01

Randomised regression 2017-01-13 – 2020-12-01

Data 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

Emulators and surrogate models via ML Shortcuts in scientific simulation using ML 2020-08-12 – 2020-08-26

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

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

Phase retrieval I’ve got the power. / Like the crack of the whip/ I snap attack/ Front to back 2017-01-16 – 2019-11-07

Fourier interpolation 2019-06-19

Clustering 2015-05-22 – 2016-06-07