Search Results for "level set method"
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Showing 89 open source projects for "level set method"
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MTEB
MTEB: Massive Text Embedding Benchmark
...Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings to date. We find that no particular text embedding method dominates across all tasks. This suggests that the field has yet to converge on a universal text embedding method and scale it up sufficiently to provide state-of-the-art results on all embedding tasks. -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. ... -
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Qiskit
Qiskit is an open-source SDK for working with quantum computers
Qiskit [kiss-kit] is an open-source SDK for working with quantum computers at the level of pulses, circuits, and application modules. When you are looking to start Qiskit, you have two options. You can start Qiskit locally, which is much more secure and private, or you get started with Jupyter Notebooks hosted in IBM Quantum Lab. Qiskit includes a comprehensive set of quantum gates and a variety of pre-built circuits so users at all levels can use Qiskit for research and application development. ... -
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GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs. -
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CCXT
JavaScript/TypeScript/Python/C#/PHP cryptocurrency trading API
The ccxt library is a collection of available crypto exchanges or exchange classes. Each class implements the public and private API for a particular crypto exchange. All exchanges are derived from the base Exchange class and share a set of common methods. To access a particular exchange from ccxt library you need to create an instance of corresponding exchange class. Supported exchanges are updated frequently and new exchanges are added regularly. -
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whisper-timestamped
Multilingual Automatic Speech Recognition with word-level timestamps
Multilingual Automatic Speech Recognition with word-level timestamps and confidence. Whisper is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. -
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StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery of benchmarking and baseline methods, giving users flexibility in selecting forecasting approaches depending on data characteristics (trend, seasonality, intermittent demand, etc.). ... -
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OpenQASM
Quantum assembly language for extended quantum circuits
...Quantum programs are described using the measurement-based quantum circuit model with support for classical feed-forward flow control based on measurement outcomes. OpenQASM presents a parameterized set of physical logic gates and concurrent real-time classical computations. Its main goal is to serve as an intermediate representation for higher-level compilers to communicate with quantum hardware. Allowances have been made for human usability. In particular, the language admits different representations of the same program as it is transformed from a high-level description to a pulse representation. -
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uvicorn
An ASGI web server, for Python
Uvicorn is an ASGI web server implementation for Python. Until recently Python has lacked a minimal low-level server/application interface for async frameworks. The ASGI specification fills this gap, and means we're now able to start building a common set of tooling usable across all async frameworks. Uvicorn currently supports HTTP/1.1 and WebSockets. -
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Conda
OS-agnostic, system-level binary package manager
Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a... -
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Habitat-Lab
A modular high-level library to train embodied AI agents
...Configuring and instantiating a diverse set of embodied agents, including commercial robots and humanoids, specifying their sensors and capabilities. Providing algorithms for single and multi-agent training (via imitation or reinforcement learning, or no learning at all as in SensePlanAct pipelines), as well as tools to benchmark their performance on the defined tasks using standard metrics. -
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Django
The Web framework for perfectionists with deadlines
...If you want to set up an actual deployment server, read docs/howto/deployment/index.txt for instructions. You'll probably want to read through the topical guides (in docs/topics) next; from there you can jump to the HOWTOs (in docs/howto) for specific problems, and check out the reference (docs/ref) for gory details. -
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TorchRL
A modular, primitive-first, python-first PyTorch library
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. TorchRL provides PyTorch and python-first, low and high-level abstractions for RL that are intended to be efficient, modular, documented, and properly tested. The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort. -
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PyTorch Ignite
Library to help with training and evaluating neural networks
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Less code than pure PyTorch while ensuring maximum control and simplicity. Library approach and no program's control inversion. Use ignite where and when you need. Extensible API for metrics, experiment managers, and other components. -
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Softaworks Agent Skills
A curated collection of skills for AI coding agents
...The toolkit’s modular design follows the Agent Skills format, making it easy for users to install only what’s needed via CLI installers or plugin marketplaces. Because the set spans from low-level utilities like dependency updaters to higher-level planning and communication aids, it can streamline many aspects of a developer’s day-to-day work. -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. ... -
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Dj-Rest-Auth
Authentication for Django Rest Framework
Since the introduction of django-rest-framework, Django apps have been able to serve up app-level REST API endpoints. As a result, we saw a lot of instances where developers implemented their own REST registration API endpoints here and there, snippets, and so on. We aim to solve this demand by providing dj-rest-auth, a set of REST API endpoints to handle User Registration and Authentication tasks. By having these API endpoints, your client apps such as AngularJS, iOS, Android, and others can communicate to your Django backend site independently via REST APIs for User Management. ... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. ... -
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Grounded-Segment-Anything
Marrying Grounding DINO with Segment Anything & Stable Diffusion
Grounded-Segment-Anything is a research-oriented project that combines powerful open-set object detection with pixel-level segmentation and subsequent creative workflows, effectively enabling detection, segmentation, and high-level vision tasks guided by free-form text prompts. The core idea behind the project is to pair Grounding DINO — a zero-shot object detector that can locate objects described by natural language — with Segment Anything Model (SAM), which can produce detailed masks for objects once they are localized. ... -
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Causal ML
Uplift modeling and causal inference with machine learning algorithms
...Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on the model form. An important lever to increase ROI in an advertising campaign is to target the ad to the set of customers who will have a favorable response in a given KPI such as engagement or sales. CATE identifies these customers by estimating the effect of the KPI from ad exposure at the individual level from A/B experiments or historical observational data. -
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ManiSkill
SAPIEN Manipulation Skill Framework
ManiSkill is a benchmark platform for training and evaluating reinforcement learning agents on dexterous manipulation tasks using physics-based simulations. Developed by Hao Su Lab, it focuses on robotic manipulation with diverse, high-quality 3D tasks designed to challenge perception, control, and planning in robotics. ManiSkill provides both low-level control and visual observation spaces for realistic learning scenarios. -
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AWS X-Ray SDK for Python
AWS X-Ray SDK for the Python programming language
...If customer wants to enable generating secure random trace and entity id for all the (sampled/unsampled) requests (this is applicable for trace id injection into logs use case) then they should set the AWS_XRAY_NOOP_ID environment variable as False. Oftentimes, it may be useful to be able to disable X-Ray for specific use cases, whether to stop X-Ray from sending traces at any moment or to test code functionality that originally depended on X-Ray instrumented packages to begin segments prior to the code call. For example, if your application relied on an XRayMiddleware to instrument incoming web requests, and you have a method that begins subsegments based on the segment generated. -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
...It’s intended for researchers exploring self-supervised and unsupervised recognition, offering a practical path to scale beyond costly labeled corpora. The README links papers and gives a high-level overview of components and expected outputs, with pointers to demos and assets. The repository is actively starred and structured as a typical research release with license, contribution guidelines, and security policy. -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,... -
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Manim Skills Repository
Agent skills for Manim to create 3Blue1Brown style animations
...The project aims to wrap common animation logic into structured skills that can be invoked programmatically, reducing boilerplate and allowing creators to focus on creative content rather than low-level animation setup. With clear installation instructions and a collection of test cases, it’s approachable for developers comfortable with Python and interested in educational or technical visualization.
