Neural Nets

Function approximators.

Generative music with language+diffusion models 2022-09-16 – 2023-12-06

Neural denoising diffusion models Denoising diffusion probabilistic models (DDPMs), score-based generative models, generative diffusion processes, neural energy models… 2021-11-11 – 2023-12-06

System identification in continuous time Learning in continuous ODEs, SDEs and CDEs 2016-08-01 – 2023-11-30

Machine learning for partial differential equations 2017-05-15 – 2023-11-17

Generative industrial design 2022-09-16 – 2023-11-13

Causal inference in highly parameterized ML 2020-09-18 – 2023-10-24

Physics-informed neural networks 2019-10-15 – 2023-10-19

Neural PDE operator learning Especially forward operators. Image-to-image regression, where the images encode a physical process. 2019-10-15 – 2023-10-19

Pytorch #torched 2018-05-04 – 2023-10-17

Technological singularities Incorporating hard AI take-offs, game-over high scores, the technium, deus-ex-machina, deus-ex-nube, nerd raptures and so forth 2016-12-01 – 2023-10-11

Gradient flows infinitesimal optimization 2020-01-30 – 2023-09-28

Probabilistic numerics 2023-07-13 – 2023-09-25

Machine learning for climate systems 2020-04-02 – 2023-09-25

Code generation, programming assistants 2021-10-14 – 2023-08-28

Browser machine learning 2017-01-13 – 2023-08-22

ML on small devices Putting intelligence on chips small enough to be in disconcerting places 2016-10-14 – 2023-08-14

Materials informatics Machine learning in condensed matter physics, chemistry and materials science 2023-08-01 – 2023-08-08

Snowmobile or bicycle? Complement or substitute? 2023-03-23 – 2023-08-07

Economics of large language models 2023-03-23 – 2023-08-07

Generative art with language+diffusion models 2022-09-16 – 2023-07-16

Bayes neural nets via subsetting weights 2017-01-11 – 2023-07-03

Neural nets with implicit layers Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem 2020-12-08 – 2023-06-28

Position encoding Also Fourier features 2021-01-21 – 2023-06-23

Neural nets that do symbolic maths 2019-12-09 – 2023-06-14

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

Statistical mechanics of statistics 2016-12-01 – 2023-06-02

Recurrent / convolutional / state-space Translating between means of approximating time series dynamics 2016-04-05 – 2023-05-24

Neural learning dynamical systems 2018-08-13 – 2023-05-23

Gradient descent, first-order, stochastic a.k.a. SGD, as seen in deep learning 2020-01-30 – 2023-05-19

Multi-objective optimisation 2021-07-14 – 2023-05-04

Probabilistic neural nets Bayesian and other probabilistic inference in overparameterized ML 2017-01-11 – 2023-04-27

Neural implicit representations Neural nets as coordinate mappings 2021-01-21 – 2023-04-26

Dynamics of recommender systems and other AI social interventions at societal scale Variational approximations to high modernism 2023-07-03 – 2023-04-26

Generative AI workflows and hacks 2023-03-23 – 2023-04-26

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

MLP-Mixer neural networks 2021-11-21 – 2023-03-30

Transformer networks The transformer-powered subtitle for this article is “Our most terrifyingly effective weapon against the forces of evil is our ability to laugh at them.” 2017-12-20 – 2023-03-22

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

Symbolic regression 2023-03-14

Generative flow nets Gflownets 2021-11-11 – 2023-02-13

Last-layer Bayes neural nets Bayesian and other probabilistic inference in overparameterized ML 2017-01-11 – 2023-02-09

Implementing neural nets 2016-10-14 – 2023-01-27

Statistics and ML in python 2015-04-27 – 2023-01-18

Graph neural nets 2020-09-16 – 2022-12-19

Machine learning for physical sciences Turbulent mixing at the boundary between disciplines with differing inertia and viscosity 2017-05-15 – 2022-12-07

Deep learning as a dynamical system 2018-08-13 – 2022-10-30

The edge of chaos Computation, evolution, competition and other past-times of faculty 2016-12-01 – 2022-10-30

Neural tangent kernel 2020-12-09 – 2022-10-14

Score matching 2021-11-11 – 2022-09-23

Ensemble Kalman methods for training neural networks Data assimilation for network weights 2022-09-20

Neural nets with implicit layers Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem 2020-12-08 – 2022-08-09

Learning Gamelan 2016-04-05 – 2022-08-05

Neural net attention mechanisms On brilliance through selective ignorance 2017-12-20 – 2022-08-05

Neural learning for spatiotemporal systems 2020-09-16 – 2022-07-28

Gradient descent, Newton-like 2019-02-05 – 2022-07-25

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

Machine learning and statistics in Julia 2019-11-27 – 2022-05-27

Probabilistic neural nets Inferring distributions in neural nets 2017-01-11 – 2022-04-07

Reservoir Computing 2022-03-28

Differentiable learning of automata 2016-10-14 – 2022-02-19

Neural nets with basis decomposition layers 2021-03-09 – 2022-02-01

Here’s how I would do art with machine learning if I had to 2016-06-06 – 2022-02-01

Running neural nets backwards 2022-01-29

Feedback system identification, linear 2016-07-27 – 2022-01-21

Garbled highlights from NeurIPS 2021 2021-11-05 – 2021-12-15

Gradient descent, Newton-like, stochastic 2020-01-23 – 2021-12-09

Ensembling neural nets Monte Carlo 2020-12-14 – 2021-11-25

Convolutional neural networks 2017-11-10 – 2021-11-21

Deep generative models 2020-12-10 – 2021-11-11

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

Regularising neural networks Generalisation for street fighters 2017-02-12 – 2021-09-24

Economics of automation When to the robots come for my job? 2021-09-20

Recurrent neural networks 2016-06-16 – 2021-09-06

Neural network activation functions 2017-01-12 – 2021-08-02

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

Multi-task ML 2021-07-14

Tensorflow The framework to use for deep learning if you groupthink like Google 2016-07-11 – 2021-07-07

ML Koans Passing through the NAND-gate 2021-06-23

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

Compressing neural nets pruning, compacting and otherwise fitting a good estimate into fewer parameters 2016-10-14 – 2021-05-07

ML benchmarks and their pitfalls On marginal efficiency gain in paperclip manufacture 2020-08-16 – 2021-04-13

Memory in machine learning 2021-03-03 – 2021-03-03

Why does deep learning work? Are we in the pocket of Big VRAM? 2017-05-30 – 2020-12-14

Garbled highlights from NeurIPS 2020 2020-09-17 – 2020-12-11

Big data ML best practice 2020-09-16 – 2020-09-21

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

Neural nets Designing the fanciest usable differentiable loss surface 2016-10-14 – 2020-09-09

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

Deep fakery 2020-06-15

Teaching computers to write music 2016-06-06 – 2020-03-25

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

Gradient descent, Higher order 2019-10-26

Garbled highlights from NIPS 2016 2016-12-05 – 2017-02-03

Dynamical systems 2016-04-26 – 2016-07-27

Pattern machine 2011-06-27 – 2015-11-24