# optimization

Pytorch #torched 2018-05-04 – 2023-10-17
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
Neural denoising diffusion models Denoising diffusion probabilistic models (DDPMs), score-based generative models, generative diffusion processes, neural energy models… 2021-11-11 – 2023-05-25
Jax Julia for python 2020-09-15 – 2023-05-12
Hyperparameter optimization Replacing a hyperparameter problem with a hyperhyperparameter problem which feels like progress 2020-09-25 – 2023-05-12
Optimal transport inference I feel the earth mover under my feet, I feel the ψ tumbling down, I feel my heart start to trembling, whenever you’re around (my barycentre) 2021-03-16 – 2023-05-03
Normalizing flows Invertible density models, sounding clever by using the word diffeomorphism like a real mathematician 2018-04-04 – 2023-05-02
Transport maps Inference by measure transport, low-dimensional coupling… 2018-04-04 – 2023-02-21
Probability divergences Metrics, contrasts and divergences and other ways of quantifying how similar are two randomnesses 2014-11-25 – 2023-01-06
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
ELBO Evidence lower bound, variational free energy etc 2020-10-02 – 2022-08-03
SLAM Simultaneous Location and Mapping 2014-11-25 – 2022-04-28
Sparse coding Wavelets, matching pursuit, overcomplete dictionaries… 2014-11-17 – 2022-03-07
Variational inference On fitting something not too far from a pretty good model that is not too hard 2016-03-22 – 2022-02-10
Meta learning Few-shot learning, learning fast weights, learning to learn 2021-09-16
Tensorflow The framework to use for deep learning if you groupthink like Google 2016-07-11 – 2021-07-07
Stein’s method His eyes are like angels but his heart is cold / No need to ask / He’s a Stein operator 2021-03-12 – 2021-06-01
Differentiable model selection Differentiable hyperparameter search, and architecture search, and optimisation optimisation by optimisation and so on 2020-09-25 – 2021-04-13
AutoML 2017-07-17 – 2020-10-02
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
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