Python Differentiable-computing Resources

AWS Data Engineering Pipeline This is a repository for the Duke University Cloud Computing course project on Serverless Data Engineering Pipeline. For

Discord Bot that leverages the idea of nested containers using podman, runs untrusted user input, executes Quantum Circuits, allows users to refer to the Qiskit Documentation, and provides the ability to search questions on the Quantum Computing StackExchange.

GeoDoodle Geodesic distance computation for Blender meshes Table of Contents Overivew Usage Implementation Overview This addon provides an operator fo

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

LED2-Net This is PyTorch implementation of our CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering". Y

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

nvdiffmodeling Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Automatic 3D Model

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

gradsim gradSim: Differentiable simulation for system identification and visuomotor control gradSim is a unified differentiable rendering and multiphy

PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation Code repository for the paper: PoseAug: A Differentiable Pose Augme

monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical algebra libraries.

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

IPython: Productive Interactive Computing Overview Welcome to IPython. Our full documentation is available on ipython.readthedocs.io and contains info

Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl

ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures i

PyCUDA lets you access Nvidia's CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist-so what's so special about P

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

Project Home Blog Documents Paper Media Coverage Join Fiber users email list [email protected] Fiber Distributed Computing for AI Made Simp

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples

A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

⚠️ The Nimbus infrastructure project is no longer under development. ⚠️ For more information, please read the news announcement. If you are interested

Spack Spack is a multi-platform package manager that builds and installs multiple versions and configurations of software. It works on Linux, macOS, a

Scikit-Optimize Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements

swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. Blog posts Release 1.0.0 Fir

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Spack Spack is a multi-platform package manager that builds and installs multiple versions and configurations of software. It works on Linux, macOS, a

ReproZip ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used comm

Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent

UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering This repository holds all the code and data for our recent work on

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and

Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t

MDCT A fast MDCT implementation using SciPy and FFTs Installation As usual pip install mdct Dependencies NumPy SciPy STFT Usage import mdct spectrum

Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

Documentation | FAQ | Release Notes | Roadmap | MACE Model Zoo | Demo | Join Us | 中文 Mobile AI Compute Engine (or MACE for short) is a deep learning i

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

ArtEmis: Affective Language for Art Created by Panos Achlioptas, Maks Ovsjanikov, Kilichbek Haydarov, Mohamed Elhoseiny, Leonidas J. Guibas Introducti

deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo

gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing

Scaleway SDK Python SDK to query Scaleway's APIs. Stable release: Development: Installation The package is available on pip. To install it in a virtua

Dash Dash is the most downloaded, trusted Python framework for building ML & data science web apps. Built on top of Plotly.js, React and Flask, Dash t

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Couler What is Couler? Couler aims to provide a unified interface for constructing and managing workflows on different workflow engines, such as Argo

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer