Search Results for "graphs" - Page 2
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Showing 68 open source projects for "graphs"
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hithesis
LaTeX thesis template package for Harbin Institute of Technology
hithesis is a LaTeX thesis template tailored to the formatting requirements of Harbin Institute of Technology, covering undergraduate, master’s, and doctoral submissions. It provides class files and examples that handle title pages, abstracts in multiple languages, acknowledgments, lists of figures/tables, symbols, and properly styled chaptering. The template includes bibliography settings and citation styles that conform to school rules, along with ready-made environments for formulas,... -
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ProbabilisticCircuits.jl
Probabilistic Circuits from the Juice library
This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units). Given certain structural properties, PCs enable different range of tractable exact probabilistic queries such as computing marginals, conditionals, maximum a posteriori (MAP), and more advanced probabilistic queries. -
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Yangshun Lago
Data Structures and Algorithms library in TypeScript and JavaScript
Lago is a study-oriented library of classic data structures and algorithms implemented in JavaScript with an emphasis on readability and learning. Instead of aiming to be a production runtime, it serves as a reference you can step through to understand how arrays, stacks, queues, linked lists, trees, heaps, graphs, and sorting/searching routines actually work. The implementations favor clarity over micro-optimizations, making them approachable for learners who are new to algorithmic thinking or coming from non-CS backgrounds. Because the code is idiomatic JavaScript, it also helps front-end engineers strengthen fundamentals without switching languages. ... -
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YCharts
YCharts is a graph library for Android
YCharts is a Jetpack-compose-based charts library that enables developers to easily integrate various types of charts/graphs into their existing UI to visually represent statistical data. YCharts supports both cartesian(XY-charts) and polar charts(Radial charts). -
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Svelvet
A library for building dynamic, infinitely customizable interfaces
Build interactive, node-based UIs and diagrams in Svelte. Svelvet is a lightweight component library for building dynamic, customizable node graphs. Svelvet allows you to easily create intuitive user interfaces and diagrams with pre-built components with node-to-node data flow, seamless zooming and panning, customizable edges and nodes and more. Start mapping out your ideas with our NPM package. Simply provide your node data to the Svelvet component and you're ready to show off your interactive diagram - no extra configuration needed. ... -
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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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Jadecy
Java lib to compute (code) deps, SCCs, and cycles (Johnson algorithm).
Jadecy (Java Dependencies and Cycles) is a Java library to compute dependencies (elements depended on, or depending), strongly connected components, and cycles, in general directed graphs, or classes or packages dependencies graphs parsed from class files (major version <= 52, else does best effort). It uses Tarjan's algorithm for SCCs computation, and Johnson's algorithm for exhaustive cycles computation, with continuations instead of recursion, which allows to handle large graphs (< 2^31 vertices). Since version 1.1, can also compute shortest cycles covering all edges of SCCs. ... -
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QuickChart
Chart image and QR code web API
...Let's get creative! You can use all static customization options available in Chart.js. Visit our chart gallery to see different chart types and plugins: bar charts, line graphs, pie charts, and much more. QuickChart easily integrates with many no-code tools. Use our no-code chart maker to create custom chart templates that you can embed dynamically in spreadsheets, Airtable, Bubble, AppSheet, Thunkable, and many other no-code tools. Rendering at scale is difficult and resource intensive. We've put a lot of working into taking care of the most difficult parts so you can focus on building your application. -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. For someone trying to get up to speed... -
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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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LeetCode
LeetCode Problems' Solutions
...It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how common interview problems can be implemented in code. Because it is a solution archive, it is best used as a learning companion after attempting problems independently. Its main value is providing a broad, accessible reference set for developers preparing for coding interviews. -
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Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. -
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Plumbing
Prismatic's Clojure(Script) utility belt
Plumbing is a general-purpose Clojure utility belt and data transformation library endorsed for its pragmatic approach to everyday tasks. It offers a toolkit of macros and functions that simplify common data manipulation patterns, and includes a “Graph” abstraction for structured computation flows. Most of it is also compatible with ClojureScript. Graph is a simple and declarative way to specify a structured computation, which is easy to analyze, change, compose, and monitor. Here's a simple... -
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libRSF
A robust sensor fusion library for online localization
The libRSF is an open source C++ library that provides several components that are required to estimate the state of a (robotic) system based on probabilistic methods. By applying the factor graph concept, well known from Graph SLAM, libRSF provides a robust solution for many sensor fusion problems. The general idea of factor graphs is to describe the state estimation problem as a graph of nodes (the state variables) that are connected by factors (measurements). The resulting graph optimization problem can be solved by applying non-linear least squares optimization. -
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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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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. ... -
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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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VivaGraph
Graph drawing library for JavaScript
...VivaGraphJS is modular, so you can extend or customize layouts, rendering, and interaction logic to fit specialized applications such as social network analysis, dependency mapping, or knowledge graphs. -
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Incremental DOM
An in-place DOM diffing library
Incremental DOM is a lightweight library for building DOM trees by issuing imperative update instructions, avoiding heavyweight virtual DOM diffing at runtime. Instead of creating and diffing large object graphs, templates compile to a sequence of function calls that “patch” the live DOM in place. This model eliminates allocations associated with virtual trees and allows updates to be streamed directly to the DOM, which can improve memory usage and reduce GC pressure. It integrates naturally with template compilers (such as those that generate calls from HTML-like markup) but can also be used by hand for fine-tuned rendering. ... -
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Your basic graph
Graph algorithms and data structures
...This text is about the implementation of a Go tool based entirely on functions – the API contains only immutable data types, and the code is built on top of a struct with five function fields. It’s a tool for building virtual graphs. In a virtual graph no vertices or edges are stored in memory, they are instead computed as needed. The tool is part of a larger library of generic graph algorithms. -
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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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Satsuma .NET Graph Library
a delicious .NET graph library
Satsuma is a graph library for .NET, written in C#. Satsuma is an easy-to-use and flexible library, which implements all the necessary graph structures, and the fastest possible graph algorithms. DOCUMENTATION: http://satsumagraph.sourceforge.net/ Satsuma is not a charting library. 'Graph' is used in the mathematical sense here (e.g. nodes connected with arcs). Satsuma is released under the zlib license. This license is very permissive and allows you to use Satsuma for both personal... -
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Linode Longview
Linode Longview Agent
Linode Longview is a system-level statistics collection and graphing service powered by an open-source agent that can be installed on any Linux system. It collects system statistics and sends them to Linode, where the data is stored and presented in meaningful ways. -
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The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classification and indexing.
