shokoryu

bincode

A binary encoder / decoder implementation in Rust.

curl-impersonate

curl-impersonate: A special build of curl that can impersonate Chrome & Firefox

erg

A statically typed language compatible with Python

freemocap

Free Motion Capture for Everyone 💀✨

OSlash

Functors, Applicatives, And Monads in Python

tuplex

Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather than invoking the Python interpreter, Tuplex generates optimized LLVM bytecode for the given pipeline and input data set.

parallax

ts_tutorial

mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

easy-neural-ode

Code for the paper "Learning Differential Equations that are Easy to Solve"

torchsde

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

DeepHPMs

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

ParticleFlowBayesRule

Pytorch implementation for "Particle Flow Bayes' Rule"

geometry-central

Applied 3D geometry in C++, with a focus on surface meshes.

computation-thru-dynamics

Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.

gradient-estimators-in-stochastic-computation-graphs

Gradient Estimation in Stochastic Computation Graphs using TensorFlow.

DifferentialEquations.jl

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

causal_learning_unknown_interventions

Code for "Neural causal learning from unknown interventions"

crash-model

Build a crash prediction modeling application that leverages multiple data sources to generate a set of dynamic predictions we can use to identify potential trouble spots and direct timely safety interventions.

CEVAE

Causal Effect Inference with Deep Latent-Variable Models

bayesian-machine-learning

Notebooks about Bayesian methods for machine learning

JaxEnt

Jax-based MaxEnt

bdl-benchmarks

Bayesian Deep Learning Benchmarks

Brancher

A python library for stochastic variational inference and differentiable probabilistic programming

gp-infer-net

Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019

river

🌊 Online machine learning in Python

ensmallen

A header-only C++ library for numerical optimization --

FBNN

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

ML-SGHMC

Experiment code for Stochastic Gradient Hamiltonian Monte Carlo

PyTorch-BayesianCNN

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.