Linux kernel source tree

A Python package for probabilistic state space modeling with JAX

A fast and flexible Python package for efficiently solving lasso, elastic net, group lasso, and group elastic net problems.

Official JAX implementation of xLSTM including fast and efficient training and inference code. 7B model available at https://huggingface.co/NX-AI/xLSTM-7b.

Gaussian processes in JAX and Flax.

Machine Learning Methods for Neural Data Analysis

A playbook for systematically maximizing the performance of deep learning models.

COGS118C [Neural Signal Processing] @ UCSanDiego

Structural Time Series in JAX

A deep learning framework for multi-animal pose tracking.

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Poisson Identifiable VAE (pi-VAE)

Probabilistic Numerics in Python.

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

Experimental folder for state space modeling code

WIP: Python port of Kilosort2

The COntextual INference (COIN) model

Optax is a gradient processing and optimization library for JAX.

Code for Krause and Drugowitsch (2022). "A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum". Neuron.

Jax SSM Library

Implementation of https://srush.github.io/annotated-s4

Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend

Functional matrix factorization via Bayesian tensor filtering

Interactive Markov-chain Monte Carlo Javascript demos

Neuroproc dataset descriptions and dictionaries

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

YASS: Yet Another Spike Sorter