Search Results for "artificial evolution"
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Showing 84 open source projects for "artificial evolution"
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AlphaTree
DNN && GAN && NLP && BIG DATA
AlphaTree is an educational repository that provides a visual roadmap of deep learning models and related artificial intelligence technologies. The project focuses on explaining the historical development and relationships between major neural network architectures used in modern machine learning. It presents diagrams and documentation describing the evolution of models such as LeNet, AlexNet, VGG, ResNet, DenseNet, and Inception networks. The repository organizes these architectures into a structured learning path that helps learners understand how deep learning models improved over time through changes in depth, architectural complexity, and training techniques. ... -
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LobeHub
Workspace to find, build, and collaborate with AI agents
LobeHub is an all-in-one workspace designed to help humans and AI agents collaborate, grow, and evolve together. It treats AI agents as true teammates rather than one-off tools, enabling deeper context, continuity, and productivity. Users can build personalized agent teams that understand their workflows, preferences, and goals over time. LobeHub brings multiple models, tools, and modalities into a single unified environment under the user’s control. With built-in collaboration features,... -
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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... -
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llm_interview_note
Mainly record the knowledge and interview questions
llm_interview_note is an open-source knowledge repository designed to help engineers prepare for interviews and deepen their understanding of large language models (LLMs). The project compiles structured notes, conceptual explanations, and curated interview questions related to modern NLP and generative AI systems. It covers fundamental topics such as the historical evolution of language models, tokenization methods, word embeddings, and the architectural foundations of transformer-based... -
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Crush
The glamourous AI CLI coding agent for your favourite terminal 💘
Crush is a next-generation, terminal-based AI coding assistant developed by Charm, designed to seamlessly integrate with your tools, workflows, and preferred LLMs. It provides developers with an intuitive, session-based experience where multiple contexts can be managed across projects. With flexible model switching, Crush allows you to change providers mid-session while retaining conversation history. It enhances productivity by combining LSP (Language Server Protocol) support with... -
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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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KG-LLM-Papers
Papers integrating knowledge graphs (KGs) and large language models
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge... -
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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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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... -
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EvoAgentX
Self-evolving AI agent framework for automated workflows
EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. 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,... -
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LearnLLM.AI
Sharing knowledge about big models that everyone can understand
LLMForEverybody is an open-source educational repository designed to make large language model concepts accessible to a broad audience, including beginners, developers, and job candidates preparing for AI-related interviews. The project organizes knowledge about LLMs into a structured learning path that begins with foundational research papers and progresses through the evolution of modern model architectures. It covers a wide range of topics including attention mechanisms, tokenization... -
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Biogenesis Color Mod
Mod for evolution simulation and artificial life program Biogenesis
You can download the Color Mod at the Biogenesis main site too (included in the main download now). You also find the sourcecode there. If you want to post a review, remember that this is only a modification, so comment on my changes, not on the simulation. Original project by Joan Queralt Molina: https://sourceforge.net/projects/biogenesis/ Includes Tyler Colemans "Features Mod": https://sourceforge.net/projects/biogenesisfeatu/ Biogenesis discussion... -
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MLP Network Configurator
interactive tool designed to help users understand how neural network
... - Testing: Accuracy calculation, error graphs, confusion matrix, misclassified sample montage. - Camera Dataset Builder: Capture and label images live via webcam. - Model Insight: Animated weight & bias evolution, interactive heatmaps. - Save & Load: Export models and configurations for reuse and sharing. 💸 Donateware Model MLP Network Configurator is distributed as donateware: - The program is fully functional -
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Dark Mode Leakage Radar
Quantum Radar for Dark Mode Leakage Detection Standard Radar Returns
Live try: https://stealthpdpradar.streamlit.app/ Spectral duality filter that extracts green-speck entanglement residuals and blue-halo IR fusion to detect stealth objects by revealing dark-mode leakage in ordinary radar returns. Features PDP Quantum Filter: Implements photon-dark-photon kinetic mixing and von Neumann evolution Dark-Mode Leakage Detection: Reveals quantum entanglement signatures of stealth objects Blue-Halo Fusion Visualization: RGB composite highlighting... -
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Style Aligned
Official code for Style Aligned Image Generation via Shared Attention
StyleAligned is a diffusion-model editing technique and codebase that preserves the visual “style” of an original image while applying new semantic edits driven by text. 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... -
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PromptPapers
Curated list of prompt-learning papers for NLP research use
PromptPapers is a curated repository that collects and organizes influential research papers focused on prompt-based tuning for large-scale pre-trained language models. It serves as a centralized reading list for researchers and practitioners interested in modern prompt learning techniques, which differ from traditional fine-tuning by leveraging pre-trained tasks directly for prediction. PromptPapers categorizes papers into multiple sections such as overview, pilot work, basics, analysis,... -
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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. A key innovation is a new Global Response Normalization (GRN) layer added to the ConvNeXt backbone, which enhances feature... -
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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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Biogenesis is an artificial life program that simulates the processes involved in the evolution of organisms. It shows colored segment based organisms that mutate and evolve in a 2D environment. Biogenesis is based on Primordial Life.
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DomE
Implements a reference architecture for creating information systems
...Thus, an alternative to the traditional software production processes is proposed, which involves several stages and different actors, sometimes demanding a lot of time and money without obtaining the expected result. With software engineering techniques, self-adaptive systems, and artificial intelligence, it is possible, the integration between design time and execution time. -
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Ad-papers
Papers on Computational Advertising
The Ad-papers repository is a curated collection of influential research papers focused on the fields of advertising technology, recommendation systems, and applied machine learning in online platforms. The repository organizes academic and industry papers that explore how machine learning algorithms can be used to improve ad targeting, user modeling, click-through rate prediction, and personalized recommendation systems. These papers represent key developments in large-scale industrial... -
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A Machine Learning Course with Python
A course about machine learning with Python
...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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Commander
Commander.exe is speech recognition engine for Polaris.
Commander.exe is speech recognition engine for Polaris. What is Polaris ? Polaris is plugin for Eclipse IDE With Polaris you have the possibility of incorporating speech into programing. Through use of this plugin in Eclipse IDE you can see that not only is it possible to provide an environment for a programing with voice, but that programing with voice it is part of the natural evolution of programming tools. Current version supports simple but powerful commands such as openig... -
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Polaris programing with voice in Eclipse
Polaris, programing with voice in Eclipse IDE
With Polaris you have the possibility of incorporating speech into programing. Through use of this plugin in Eclipse IDE you can see that not only is it possible to provide an environment for a programing with voice, but that programing with voice it is part of the natural evolution of programming tools. VOICE COMMANDS eclipse task eclipse search eclipse skip eclipse format eclipse new eclipse save eclipse rename eclipse cut eclipse copy eclipse paste eclipse all eclipse... -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
...It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer
