krzysztofrusek

krzysztofrusek's Stars

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook43.6k1.8k19418k

• astral-sh/uv

  An extremely fast Python package and project manager, written in Rust.

  Language:Rust35.2k744.7k959

• CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

  aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

  Language:Jupyter Notebook27.1k1.4k2457.9k

• modularml/mojo

  The Mojo Programming Language

  Language:Mojo23.5k2662.3k2.6k

• google-deepmind/graphcast

  Language:Python5.6k91108685

• facebookresearch/nevergrad

  A Python toolbox for performing gradient-free optimization

  Language:Python4k58267356

• patrick-kidger/equinox

  Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

  Language:Python2.2k25482148

• google-deepmind/penzai

  A JAX research toolkit for building, editing, and visualizing neural networks.

  Language:Python1.7k181855

• google-deepmind/materials_discovery

  Language:Jupyter Notebook9214823150

• google-deepmind/chex

  Language:Python804174848

• google/temporian

  Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖

  Language:Python682125644

• google/paxml

  Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

  Language:Python464152169

• srush/Autodiff-Puzzles

  Language:Jupyter Notebook4036425

• patrick-kidger/lineax

  Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax

  Language:Python390114824

• google-deepmind/treescope

  An interactive HTML pretty-printer for machine learning research in IPython notebooks.

  Language:Python37081619

• patrick-kidger/optimistix

  Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/

  Language:Python36396415

• normal-computing/posteriors

  Uncertainty quantification with PyTorch

  Language:Python333153014

• google-deepmind/synjax

  Language:Python24313214

• endia-org/Endia

  Build and train Neural Networks in Mojo

  Language:Mojo207717

• jax-ml/bayeux

  State of the art inference for your bayesian models.

  Language:Python1945148

• srush/do-we-need-attention

  Language:TeX164817

• google-deepmind/digraph_transformer

  Language:Python1163412

• patrick-kidger/quax

  Multiple dispatch over abstract array types in JAX.

  Language:Python1129164

• jax-ml/jax-ai-stack

  Language:Python1045820

• itsdaniele/jeometric

  Graph neural networks in JAX.

  Language:Python68201

• JiaYaobo/fenbux

  A Simple Statistical Distribution Library in JAX

  Language:Python16270

• google-deepmind/ccbo

  This repo contains the code associated to the paper: "Constrained Causal Bayesian Optimization" by Aglietti Virginia, Alan Malek, Ira Ktena, and Silvia Chiappa. International Conference on Machine Learning. PMLR, 2023.

  Language:Python15402

• devvrit/SONew

  Language:Python9300

• BNN-UPC/Atom_Neural_Traffic_Compression

  This repository contains de code and instructions to train the models and prepare the datasets for the experiments in the paper "Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks" accepted at the 2nd ACM CONEXT GNNet 2023 Workshop.

  Language:Python6400

• gsd-authors/gsd

  Reference implementation of generalised score distribution in python

  Language:Python1230