Search Results for "evolution"
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Showing 54 open source projects for "evolution"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Nevergrad
A Python toolbox for performing gradient-free optimization
...Nevergrad supports parallelization, budget scheduling, and multiple cost/resource constraints, allowing it to scale to nontrivial optimization problems. It includes visualization tools and diagnostic metrics to compare strategy performance, track parameter evolution, and detect stagnation. -
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Aerich
A database migrations tool for TortoiseORM, ready to production
Aerich is a lightweight database migration tool built for Tortoise ORM, an async ORM for Python. It handles schema evolution through versioned migrations, enabling developers to update and rollback database changes with ease. Designed for asyncio-based applications, Aerich is ideal for fast-moving Python projects that need simple migration control without heavy dependencies. -
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AtomAI
Deep and Machine Learning for Microscopy
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless... -
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CloudEvents
CloudEvents Specification
Events are everywhere. However, event producers tend to describe events differently. The lack of a common way of describing events means developers must constantly re-learn how to consume events. This also limits the potential for libraries, tooling and infrastructure to aide the delivery of event data across environments, like SDKs, event routers or tracing systems. The portability and productivity we can achieve from event data is hindered overall. CloudEvents is a specification for... -
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EvoAgentX
Self-evolving AI agent framework for automated workflows
...Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows, evaluation, and evolution, enabling flexible experimentation and scaling. EvoAgentX integrates optimisation algorithms to refine prompts, tool usage, and workflow structures over time. This allows agents to adapt dynamically instead of relying on fixed logic. It is designed for researchers and developers who want to automate complex agent systems and improve performance through continuous learning cycles, reducing manual orchestration and enabling more efficient development. -
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Modoboa
Mail hosting made simple
...Modoboa is developed with modularity in mind, expanding it is really easy. Actually, all current features are extensions. It is written in Python 3 and uses the Django, jQuery and Bootstrap frameworks. Follow the evolution of your server traffic thanks to a few builtin graphics: messages distribution per type and average size. Easily use standard protocols like DKIM or DMARC to improve your sender reputation and so make sure your emails will be delivered. Consult your emails everywhere thanks to simple but functional builtin webmail. -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can... -
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ShoppingAgent
Custom Chinese chatbot with Seq2Seq, GPT, and agent features
ShoppingAgent is an open source Chinese conversational AI system that allows users to build and train their own chatbot using custom datasets. It provides multiple implementations of chatbot architectures, including traditional Seq2Seq models as well as newer GPT-style approaches, reflecting the evolution of conversational AI techniques. ShoppingAgent is structured to support experimentation across different deep learning frameworks such as TensorFlow, PyTorch, and MindSpore, giving developers flexibility in how they train and deploy models. In addition to core chatbot functionality, the project introduces agent-based capabilities, enabling practical use cases like automated workflows and task-oriented assistants. ... -
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AIBuildAI
An AI agent that automatically builds AI models
...The framework is designed to support experimentation with self-improving AI pipelines, allowing developers to test concepts like automated architecture search or adaptive system evolution. It integrates multiple components including prompt management, execution control, and feedback loops to ensure that generated outputs can be evaluated and improved over time. -
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Wan Move
Motion-controllable Video Generation via Latent Trajectory Guidance
Wan Move is an open-source research codebase for motion-controllable video generation that focuses on enabling fine-grained control of motion within generative video models. It is designed to guide the temporal evolution of visual content by leveraging latent trajectory guidance, allowing users to manipulate how objects move over time without modifying the underlying generative architecture. By representing motion information as dense point trajectories and integrating them into the latent space of an image-to-video model, the project produces videos with more precise and controllable motion behavior than many existing methods. ... -
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OpenSage
An agent framework that enables AI to create their own agent
OpenSage is an emerging open-source AI agent development framework designed to automate the creation, orchestration, and evolution of intelligent agents through a self-programming paradigm. Unlike traditional agent frameworks that require developers to manually define workflows, tools, and structures, OpenSage introduces a system where large language models can dynamically generate their own agent architectures, including sub-agents, toolchains, and execution strategies. -
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EKS Best Practices
A best practices guide for day 2 operations
The Amazon EKS Best Practices Guide is a public repository containing comprehensive documentation and guidance for operating production-grade Kubernetes clusters on AWS’s managed service, Amazon EKS. Rather than a code library, it serves as a reference catalogue of patterns, anti-patterns, checklists and architectures across domains such as security, reliability, scalability, networking, cost optimization and hybrid cloud deployments. The repository is maintained by AWS but open to... -
13
GenX
X-Ray and Neutron Reflectivity Modeling
GenX is a scientific program to refine x-ray refelcetivity, neutron reflectivity and surface x-ray diffraction data using the differential evolution algorithm. GenX is very modular and highly extensible and can be used as a general fitting program. -
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QUCAS-PDP Astronomical Image Framework
After 4/15/26 this project will be archived as 9 pipelines are conso
... 📸 Live Demo The application is deployed on Streamlit Cloud: Live App test now: https://huggingface.co/spaces/QCAUS/QCAUS QCI AstroEntangle Refiner – FDM soliton physics & image processing Magnetar QED Explorer – Magnetar fields, dark photons & vacuum QED Primordial Photon–DarkPhoton Entanglement – Von Neumann evolution in an expanding universe QCIS (Quantum Cosmology Integration Suite) – Quantum‑corrected cosmological perturbations 🔭 Overview These four projects form a complete computational framework for quantum‑inspired astrophysics. Together they enable: Image analysis of galaxy clusters (Abell, Bullet, etc.) using Fuzzy Dark Matter (FDM) soliton overlays. ... -
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Fosite - advection problem solver
numerical simulation code for solving transport equations in 1D/2D/3D
...The underlying numerical solution method belongs to the family of unsplit conservative finite volume TVD schemes. The method is 2nd order accurate in space and uses high order Runge-Kutta and multistep schemes for time evolution. In addition to the pure advection code several source terms have been implemented including viscous diffusion and gravitational acceleration. Fosite is written with object-oriented patterns in Fortran 2003 and follows the Structure of Arrays (SoA) layout, operating on generic field datatypes. This allows for high performance on modern architectures (SIMD). ... -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
...The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts. -
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Style Aligned
Official code for Style Aligned Image Generation via Shared Attention
...Instead of fully re-generating an image—and risking changes to lighting, texture, or rendering choices—the method aligns internal features across denoising steps so the target edit inherits the source style. This alignment acts like a constraint on the model’s evolution, steering composition, palette, and brushwork even as objects or attributes change. The result is more consistent edits across a set, which is crucial for workflows like product variations, character sheets, or brand-coherent art. The repository provides reproducible scripts, reference prompts, and guidance for tuning strengths so users can dial in subtle retouches or bolder substitutions. ... -
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ConvNeXt V2
Code release for ConvNeXt V2 model
ConvNeXt V2 is an evolution of the ConvNeXt architecture that co-designs convolutional networks alongside self-supervised learning. The V2 version introduces a fully convolutional masked autoencoder (FCMAE) framework where parts of the image are masked and the network reconstructs the missing content, marrying convolutional inductive bias with powerful pretraining. -
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical... -
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ety
A Python module to discover the etymology of words
...It is built as both a reusable module and a CLI utility, making it suitable for integration into other applications or standalone use. The project relies on structured datasets that map relationships between words and languages, enabling systematic exploration of linguistic evolution. It is particularly useful for developers, linguists, and researchers interested in historical language patterns and word origins. -
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DomE
Implements a reference architecture for creating information systems
DomE Experiment is an implementation of a reference architecture for creating information systems from the automated evolution of the domain model. The architecture comprises elements that guarantee user access through automatically generated interfaces for various devices, integration with external information sources, data and operations security, automatic generation of analytical information, and automatic control of business processes. All these features are generated from the domain model, which is, in turn, continuously evolved from interactions with the user or autonomously by the system itself. ... -
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Ad-papers
Papers on Computational Advertising
...These papers represent key developments in large-scale industrial machine learning systems used by digital advertising platforms. The repository categorizes papers by topic and provides links to research publications, allowing readers to easily explore the evolution of machine learning techniques in advertising and recommendation domains. Many of the included papers originate from major technology companies and research institutions that have contributed foundational work in applied machine learning systems. -
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C++QED
A framework for simulating open quantum dynamics
...The basic idea is to allow users to build arbitrarily complex interacting quantum systems out of free subsystems and interactions (elements), and simulate their time evolution with a number of available time-evolution drivers. C++QEDv2 specifies a small grammar to describe composite quantum systems. Apart from providing a number of elements out of the box, there are tools which facilitate the implementation of new elements. These are being added continuously, as the need arises. The principal concept of the design of C++QEDv2 is that all information available at compile time should be processed as such, with the help of TMP. ... -
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A Machine Learning Course with Python
A course about machine learning with Python
...In this project, we built our tutorials using many different well-known Machine Learning frameworks such as Scikit-learn. In this project you will learn what is the definition of Machine Learning? When it started and what is the trending evolution? What are the Machine Learning categories and subcategories? What are the mostly used Machine Learning algorithms and how to implement them? -
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powerfactory-fmu
The FMI++ PowerFactory FMU Export Utility
...Additional files (e.g., time series files) and start values for exported variables can be specified. Currently, two types of simulations are supported: In quasi-static steady-state simulations a power system’s evolution with respect to time is captured by a series of load flow snapshots. RMS simulations allow to calculate the time-dependent dynamics of electromechanical models, including control devices (new in version v0.6).
