Search Results for "graphs" - Page 2
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Showing 46 open source projects for "graphs"
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. ... -
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FuzzBench
FuzzBench - Fuzzer benchmarking as a service
...The service includes an easy-to-use API for integrating custom fuzzers and an automated reporting system that generates detailed statistical analyses, comparative graphs, and significance testing. By running experiments at Google scale, FuzzBench ensures consistent, unbiased, and data-driven evaluations that support academic and industrial fuzzing research. -
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Kanbanara
Web-based Project Management System using the Kanban methodology
...Its Kanban board features projects, user-definable workflow with custom states, support for epic, feature, story, enhancement, defect, task, test, bug and transient cards, global and personal WIP limits, role-based columns (Owner, Reviewer or Quality Assurance), support for ghost cards (cards on their way to you or your own cards currently being reviewed or in QA), blockable cards, hidable cards, deferable cards, 46 card styles including a customisable one, 14-day future projection, Gantt Chart andcard backdrops. It also features a hierarchical workflow, global filter, backlog pyramid, force-directed graphs utilising d3.js, report generator, routine card manager, pair programming, support for continuing cards from one project to another. Full documentation in HTML and EPUB formats. -
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Jraph
A Graph Neural Network Library in Jax
...It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time compilation. The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. Jraph also comes with a model zoo—a collection of forkable reference implementations of common message-passing GNN architectures, such as Graph Networks, Graph Convolutional Networks, and Graph Attention Networks. -
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Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target... -
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OpenNum
OpenNum lets you distribute solvers with a nice graphical interface
...More specifically, OpenNum lets you · to collect a hierarchical dataset, · to call any executable file and · to visualize scalar and vector fields, plot graphs or show simple plain text files. It also has other useful utilities specifically designed for numerical simulation packages: · it allows managing a centralized materials dataset; · it can read several finite element mesh formats and several field formats. -
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gradslam
gradslam is an open source differentiable dense SLAM library
...However, learning representations for SLAM has been an open question, because traditional SLAM systems are not end-to-end differentiable. In this work, we present gradSLAM, a differentiable computational graph take on SLAM. Leveraging the automatic differentiation capabilities of computational graphs, gradSLAM enables the design of SLAM systems that allow for gradient-based learning across each of their components, or the system as a whole. -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
...The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. It serves both as a self-study path and as a warm-up bank for interview prep or coding katas. -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. ... -
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Miasm
Reverse engineering framework in Python
...Among them, the SSA/Out-of-SSA transformation, expression propagation and high-level operators can be joined to “lift” Miasm IR to a more human-readable language. We use graphviz to illustrate some graphs. Its layout does not always totally conform with a reverse engineering “ideal view”, so please be tolerant of those odd graphs. Miasm is not the first tool to implement this feature. But, well, as the tool already had everything needed to implement DSE, it was just a matter of time before these features landed in the main branch. -
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TestRest
TestRest is a fully QA Management Tool
TestRest is Test Management offers test case authoring, reusable test cases, test execution and reporting. TestRest supports statistic and graph reports with simple modern UI interfaces. -
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Python Taint
Static Analysis Tool for Detecting Security Vulnerabilities in Python
Static analysis of Python web applications based on theoretical foundations (Control flow graphs, fixed point, dataflow analysis) Detect command injection, SSRF, SQL injection, XSS, directory traveral etc. A lot of customization is possible. For functions from builtins or libraries, e.g. url_for or os.path.join, use the -m option to specify whether or not they return tainted values given tainted inputs, by default this file is used. -
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Gin Config
Gin provides a lightweight configuration framework for Python
Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter... -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. ... -
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HyperSQL is like a doxygen plus javadoc for SQL, hypermapping SQL views, packages, procedures, and functions to HTML source code listings and showing all code locations where these are used.
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Klonwerk
advanced variability management tool
Klonwerk is an advanced and easy-to-use tool for reactive variability management and large-scale software reuse. It allows you to automatically clone and modify directories of textural or binary files (e.g. code, architecture, documentation), based on conceptual feature/decision models. -
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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A generic purpose library in Python. It includes directed graphs, dependency graphs, threads-related algorithms, etc.
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Mantikhor is an *information representation* language. Like RDF, it models information as directed-edge arc-node graphs, although Mantikhor's use of such constructs is more structured and constrained.
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A simple (~20 line python) O(n^6) algorithm for the traveling salesman problem that seems to do pretty well for most graphs; so well that I have not been able to find a graph which it does optimally solve. Those with spare cycles are welcome to help out.
