# Neural Nets

Generative music with language+diffusion models
2022-09-16
– 2023-12-06Neural denoising diffusion models
Denoising diffusion probabilistic models (DDPMs), score-based generative models, generative diffusion processes, neural energy models…
2021-11-11
– 2023-12-06System identification in continuous time
Learning in continuous ODEs, SDEs and CDEs
2016-08-01
– 2023-11-30Machine learning for partial differential equations
2017-05-15
– 2023-11-17Generative industrial design
2022-09-16
– 2023-11-13Causal inference in highly parameterized ML
2020-09-18
– 2023-10-24Physics-informed neural networks
2019-10-15
– 2023-10-19Neural PDE operator learning
Especially forward operators. Image-to-image regression, where the images encode a physical process.
2019-10-15
– 2023-10-19Pytorch
#torched
2018-05-04
– 2023-10-17Technological 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
– 2023-10-11Gradient flows
infinitesimal optimization
2020-01-30
– 2023-09-28Probabilistic numerics
2023-07-13
– 2023-09-25Machine learning for climate systems
2020-04-02
– 2023-09-25Code generation, programming assistants
2021-10-14
– 2023-08-28Browser machine learning
2017-01-13
– 2023-08-22ML on small devices
Putting intelligence on chips small enough to be in disconcerting places
2016-10-14
– 2023-08-14Materials informatics
Machine learning in condensed matter physics, chemistry and materials science
2023-08-01
– 2023-08-08Snowmobile or bicycle?
Complement or substitute?
2023-03-23
– 2023-08-07Economics of large language models
2023-03-23
– 2023-08-07Generative art with language+diffusion models
2022-09-16
– 2023-07-16Bayes neural nets via subsetting weights
2017-01-11
– 2023-07-03Neural nets with implicit layers
Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem
2020-12-08
– 2023-06-28Position encoding
Also Fourier features
2021-01-21
– 2023-06-23Neural nets that do symbolic maths
2019-12-09
– 2023-06-14Neural vector embeddings
Hyperdimensional Computing, Vector Symbolic Architectures, Holographic Reduced Representations
2017-12-20
– 2023-06-13Statistical mechanics of statistics
2016-12-01
– 2023-06-02Recurrent / convolutional / state-space
Translating between means of approximating time series dynamics
2016-04-05
– 2023-05-24Neural learning dynamical systems
2018-08-13
– 2023-05-23Gradient descent, first-order, stochastic
a.k.a. SGD, as seen in deep learning
2020-01-30
– 2023-05-19Multi-objective optimisation
2021-07-14
– 2023-05-04Probabilistic neural nets
Bayesian and other probabilistic inference in overparameterized ML
2017-01-11
– 2023-04-27Neural implicit representations
Neural nets as coordinate mappings
2021-01-21
– 2023-04-26Dynamics of recommender systems and other AI social interventions at societal scale
Variational approximations to high modernism
2023-07-03
– 2023-04-26Generative AI workflows and hacks
2023-03-23
– 2023-04-26Model order reduction
2015-03-22
– 2023-04-21MLP-Mixer neural networks
2021-11-21
– 2023-03-30Transformer 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
– 2023-03-22Deep sets
invariant and equivariant functions
2022-11-24
– 2023-03-21Symbolic regression
2023-03-14Generative flow nets
Gflownets
2021-11-11
– 2023-02-13Last-layer Bayes neural nets
Bayesian and other probabilistic inference in overparameterized ML
2017-01-11
– 2023-02-09Implementing neural nets
2016-10-14
– 2023-01-27Statistics and ML in python
2015-04-27
– 2023-01-18Graph neural nets
2020-09-16
– 2022-12-19Machine learning for physical sciences
Turbulent mixing at the boundary between disciplines with differing inertia and viscosity
2017-05-15
– 2022-12-07Deep learning as a dynamical system
2018-08-13
– 2022-10-30The edge of chaos
Computation, evolution, competition and other past-times of faculty
2016-12-01
– 2022-10-30Neural tangent kernel
2020-12-09
– 2022-10-14Score matching
2021-11-11
– 2022-09-23Ensemble Kalman methods for training neural networks
Data assimilation for network weights
2022-09-20Neural nets with implicit layers
Also, declarative networks, bi-level optimization and other ingenious uses of the implicit function theorem
2020-12-08
– 2022-08-09Learning Gamelan
2016-04-05
– 2022-08-05Neural net attention mechanisms
On brilliance through selective ignorance
2017-12-20
– 2022-08-05Neural learning for spatiotemporal systems
2020-09-16
– 2022-07-28Gradient descent, Newton-like
2019-02-05
– 2022-07-25Overparameterization in large models
Improper learning, benign overfitting, double descent
2018-04-04
– 2022-05-27Machine learning and statistics in Julia
2019-11-27
– 2022-05-27Probabilistic neural nets
Inferring distributions in neural nets
2017-01-11
– 2022-04-07Reservoir Computing
2022-03-28Differentiable learning of automata
2016-10-14
– 2022-02-19Neural nets with basis decomposition layers
2021-03-09
– 2022-02-01Here’s how I would do art with machine learning if I had to
2016-06-06
– 2022-02-01Running neural nets backwards
2022-01-29Feedback system identification, linear
2016-07-27
– 2022-01-21Garbled highlights from NeurIPS 2021
2021-11-05
– 2021-12-15Gradient descent, Newton-like, stochastic
2020-01-23
– 2021-12-09Ensembling neural nets
Monte Carlo
2020-12-14
– 2021-11-25Convolutional neural networks
2017-11-10
– 2021-11-21Deep generative models
2020-12-10
– 2021-11-11Random neural networks
2017-02-17
– 2021-10-12Regularising neural networks
Generalisation for street fighters
2017-02-12
– 2021-09-24Economics of automation
When to the robots come for my job?
2021-09-20Recurrent neural networks
2016-06-16
– 2021-09-06Neural network activation functions
2017-01-12
– 2021-08-02Learning summary statistics
2020-04-22
– 2021-07-15Multi-task ML
2021-07-14Tensorflow
The framework to use for deep learning if you groupthink like Google
2016-07-11
– 2021-07-07ML Koans
Passing through the NAND-gate
2021-06-23Infinite width limits of neural networks
2020-12-09
– 2021-05-11Compressing neural nets
pruning, compacting and otherwise fitting a good estimate into fewer parameters
2016-10-14
– 2021-05-07ML benchmarks and their pitfalls
On marginal efficiency gain in paperclip manufacture
2020-08-16
– 2021-04-13Memory in machine learning
2021-03-03
– 2021-03-03Why does deep learning work?
Are we in the pocket of Big VRAM?
2017-05-30
– 2020-12-14Garbled highlights from NeurIPS 2020
2020-09-17
– 2020-12-11Big data ML best practice
2020-09-16
– 2020-09-21Data 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
– 2020-09-11Neural nets
Designing the fanciest usable differentiable loss surface
2016-10-14
– 2020-09-09Emulators and surrogate models via ML
Shortcuts in scientific simulation using ML
2020-08-12
– 2020-08-26Learning of manifolds
Also topological data analysis; other hip names to follow
2014-08-19
– 2020-06-23Deep fakery
2020-06-15Teaching computers to write music
2016-06-06
– 2020-03-25Learnable indexes and hashes
2018-01-12
– 2020-02-18Phase retrieval
I’ve got the power. / Like the crack of the whip/ I snap attack/ Front to back
2017-01-16
– 2019-11-07Gradient descent, Higher order
2019-10-26Garbled highlights from NIPS 2016
2016-12-05
– 2017-02-03Dynamical systems
2016-04-26
– 2016-07-27Pattern machine
2011-06-27
– 2015-11-24