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Showing 2179 open source projects for "source"
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Tequila
A High-Level Abstraction Framework for Quantum Algorithms
Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices. -
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Orca Core
Core Python Controller of the ORCA Hand
Orca Core is the central Python control framework for the ORCA Hand, an open-source dexterous robotic hand designed to replicate human-like manipulation capabilities. It provides a high-level abstraction layer over the underlying hardware, allowing developers to interact with the robotic system through simplified joint-space commands rather than low-level motor instructions. The software includes a suite of scripts for calibration, tensioning, and positioning, ensuring that the physical hand operates accurately and consistently across different configurations. ... -
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Surya
Implementation of the Surya Foundation Model for Heliophysics
Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture, thereby enabling improved space weather forecasting. ... -
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OpenFermion
The electronic structure package for quantum computers
OpenFermion is an open source library for compiling and analyzing quantum algorithms to simulate fermionic systems, including quantum chemistry. Among other functionalities, this version features data structures and tools for obtaining and manipulating representations of fermionic and qubit Hamiltonians. For more information, see our release paper. Currently, OpenFermion is tested on Mac, Windows, and Linux. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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Amazon Braket Default Simulator
An implementation of a quantum simulator that you can run locally
The Amazon Braket Default Simulator is a Python open-source library that provides an implementation of a quantum simulator that you can run locally. You can use the simulator to test quantum tasks that you construct for the Amazon Braket SDK before you submit them to the Amazon Braket service for execution. You must have the Amazon Braket SDK installed to use the local simulator. Follow the instructions in the README for setup. -
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wttr.in
The right way to check the weather
wttr.in is a console-oriented weather forecast service that supports various information representation methods like terminal-oriented ANSI-sequences for console HTTP clients (curl, httpie, or wget), HTML for web browsers, or PNG for graphical viewers. Originally started as a small project, a wrapper for wego, intended to demonstrate the power of the console-oriented services, wttr.in became a popular weather reporting service, handling tens of millions of queries daily. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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BQSKit
Berkeley Quantum Synthesis Toolkit
The Berkeley Quantum Synthesis Toolkit (BQSKit) [bis • kit] is a powerful and portable quantum compiler framework. It can be used with ease to compile quantum programs to efficient physical circuits for any QPU. A standard workflow utilizing BQSKit consists of loading a program into the framework, modeling the target QPU, compiling the program, and exporting the resulting circuit. -
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Physical Symbolic Optimization (Φ-SO)
Physical Symbolic Optimization
Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms. -
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ROMM
A beautiful, powerful, self-hosted rom manager and player
ROMM is an Android productivity launcher replacement that focuses on giving users faster, easier access to apps, contacts, and information through intuitive gestures, smart search, and contextual suggestions. It reimagines the home screen with adaptive layouts, predictive app recommendations, and dynamic organization so that frequently used tools are always within reach. The launcher includes a powerful universal search that combs through installed apps, contacts, messages, and web results... -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. BioEmu outputs structures... -
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AlphaGenome
Programmatic access to the AlphaGenome model
The AlphaGenome API provides access to AlphaGenome, Google DeepMind’s unifying model for deciphering the regulatory code within DNA sequences. This repository contains client-side code, examples, and documentation to help you use the AlphaGenome API. AlphaGenome offers multimodal predictions, encompassing diverse functional outputs such as gene expression, splicing patterns, chromatin features, and contact maps. The model analyzes DNA sequences of up to 1 million base pairs in length and can... -
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Swift Numerics
Advanced mathematical types and functions for Swift
Swift Numerics is a foundational library that extends the Swift standard library with essential numerical protocols, types, and functions needed for scientific and systems programming. It defines generic abstractions over real and complex numbers so algorithms can be written once and work across concrete floating-point types. The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics... -
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Evo 2
Genome modeling and design across all domains of life
Evo 2 is a DNA language model system designed for long-context genome modeling and biological sequence design across all domains of life. The project models DNA at single-nucleotide resolution and supports context windows of up to one million base pairs, which places it in a class of models built for very large genomic reasoning tasks. According to the repository, it uses the StripedHyena 2 architecture, was pretrained with Savanna, and was trained autoregressively on the OpenGenome2 dataset... -
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
The Mathematics Dataset, developed by Google DeepMind, is a synthetic dataset designed to evaluate and train machine learning models on mathematical reasoning and symbolic manipulation. It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear... -
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Segments.ai
Segments.ai Python SDK
Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML... -
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Cookiecutter Data Science
Project structure for doing and sharing data science work
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of... -
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CycleGAN and pix2pix in PyTorch
Image-to-Image Translation in PyTorch
CycleGAN and pix2pix in PyTorch repository is a PyTorch implementation of two influential image-to-image translation frameworks: CycleGAN (for unpaired translation) and pix2pix (for paired translation). This repo gives developers and researchers a convenient, modern (PyTorch-based) platform to train and test these methods — supporting both paired datasets (input to output) and unpaired datasets (domain-to-domain) with minimal changes. The code supports standard training and inference... -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To... -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
The library consists of various dynamic and temporal geometric deep learning, embedding, and Spatio-temporal regression methods from a variety of published research papers. Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic... -
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Vedo
A python module for scientific analysis of 3D data
A lightweight and powerful python module for scientific analysis and visualization of 3d objects. Inspired by the vpython manifesto "3D programming for ordinary mortals", vedo makes it easy to work with 3D pointclouds, meshes and volumes, in just a few lines of code, even for less experienced programmers. vedo is based on VTK and numpy, with no other dependencies. Import meshes from VTK format, STL, Wavefront OBJ, 3DS, Dolfin-XML, Neutral, GMSH, OFF, PCD (PointCloud). Export meshes as ASCII... -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations,... -
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Napkin
An Infinitely Large Napkin
Napkin (also titled “An Infinitely Large Napkin”) is a lightweight, semi-formal introduction to higher mathematics, aimed at giving readers a bird’s-eye view over various mathematical fields. It is not a polished textbook full of full proofs; rather it offers clean definitions, theorem statements, intuitive motivations, and informal sketches of why things work, with the goal of building conceptual understanding. The coverage spans undergraduate and early graduate topics, designed to show how...
