Search Results for "graph generator"

AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project...

...The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. Its main value is bridging natural-language mathematics with formal verification systems in a way that is more automated, inspectable, and iterative than traditional theorem-proving pipelines.

Imogen is a real-time, node-based procedural texture generation tool aimed at artists, developers, and shader enthusiasts. It allows users to build complex material textures using a graph-based interface, combining operations like blending, noise, filters, and color correction in a non-destructive workflow. Built with Vulkan and ImGui, Imogen provides immediate visual feedback and supports GPU acceleration for high-resolution texture output. It's particularly useful in game development, VFX,...

...This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the TensorFlow Hub models. This reimplementation was done from the raw computation graph of the Tensorflow version and behave similarly to the TensorFlow version (variance of the output difference of the order of 1e-5). This implementation currently only contains the generator as the weights of the discriminator were not released (although the structure of the discriminator is very similar to the generator so it could be added pretty easily.

...The repository includes training code, datasets, and evaluation scripts so researchers can reproduce baselines and extend components such as the graph encoder or image generator. In practice, sg2im demonstrates how structured semantics can guide generative models to produce controllable, compositional imagery.

...However, it is hard to detect similarity in source code especially if the number of students is high. Furthermore, it is better to prevent plagiarism before it is committed. The “Anti-Plagiarism Graph Generator” program is developed to prevent plagiarism in Graph Theory course programming assignments. The prevention is done at the very beginning before the students start to do their programming assignments. This is possible as students will get a different set of question based on their students’ identification number. Students will generate their own graph by using this program. ...

This program allows you to, very easily, generate very nice cheat sheets for in your graphical calculator. These cheat sheets will be shown in the graph screen instead of the normal screen, which allows for smaller letters and thus more text per page. They also support multiple pages, so you can put a whole lot of text inside one single cheat sheet! IMPORTANT: Exiting the cheat sheet on the calculator is done by pressing enter. If you don't do this, the graph screen will still contain...

A threaded Web graph (Power law random graph) generator written in Python. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It implements a threaded variant of the RMAT algorithm.