Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
updated at May 12, 2024, 6:25 a.m.
Fast and Easy Infinite Neural Networks in Python
updated at May 11, 2024, 11 p.m.
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
updated at May 11, 2024, 12:45 p.m.
A library for programmatically generating equivariant layers through constraint solving
updated at May 10, 2024, 10:02 a.m.
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
updated at May 9, 2024, 5:07 p.m.
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
updated at May 8, 2024, 6:50 p.m.
Functional models and algorithms for sparse signal processing
updated at May 5, 2024, 1:49 p.m.
Inverse optimal control for continuous psychophysics
updated at May 3, 2024, 2:34 p.m.
🐈 Automatic differentiable spectrum modeling of exoplanets/brown dwarfs using JAX, compatible with NumPyro and JAXopt
updated at April 27, 2024, 9:02 p.m.
JAX + Flax implementation of "Combinatorial Optimization with Physics-Inspired Graph Neural Networks" by Schuetz et al.
updated at April 22, 2024, 11:11 a.m.
How to use the Flax Linen API to build a convolutional neural network model and train it for image classification (using TensorFlow Datasets).
updated at March 31, 2024, 6:02 p.m.
Nested Hierarchical Transformer https://arxiv.org/pdf/2105.12723.pdf
updated at March 28, 2024, 10:26 a.m.