MLP classifier on the MNIST dataset implemented in JAX with a GUI for entering hyperparameters, and a custom visualization of runs on TensorBoard.
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Updated
Feb 26, 2024 - Python
MLP classifier on the MNIST dataset implemented in JAX with a GUI for entering hyperparameters, and a custom visualization of runs on TensorBoard.
Optimal feedback control + interventions, in JAX.
Simple Python application to observe effects of obliquity and eccentricity on equation of time and analemma
Markov Chain Cubature via JAX. Efficient SDE solving and Bayesian inference.
Single-file SAC-N implementation on jax with flax and equinox. 10x faster than pytorch
Multiple dispatch over abstract array types in JAX.
Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/
Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
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