Search Results for "squid-graph" - Page 3
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Showing 86 open source projects for "squid-graph"
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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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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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TFLearn
Deep learning library featuring a higher-level API for TensorFlow
...Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations, and more. Effortless device placement for using multiple CPU/GPU. The high-level API currently supports the most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, etc. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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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.
...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. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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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. ... -
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ArangoDB Interactive Tutorials
Repository for all ArangoDB interactive tutorial notebooks
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Pinject
A pythonic dependency injection library
...Because bindings are just Python functions and classes, refactoring remains straightforward and the DI graph is easy to reason about. Pinject is particularly useful for medium-to-large services where configuration, logging, data clients, and business logic need clean separation without resorting to manual plumbing. -
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VivaGraph
Graph drawing library for JavaScript
VivaGraphJS is a powerful, high-performance graph drawing library for JavaScript that enables developers to visualize complex networks directly in the browser or in Node.js environments. It is designed for speed and scalability, handling large graph datasets with smooth rendering and interactive capabilities such as dragging nodes and zooming. The library supports multiple rendering backends including SVG, WebGL, and Canvas, allowing developers to choose the best balance of performance and visual fidelity for their use case. ... -
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Mount
managing Clojure and ClojureScript app state since (reset)
Mount is a lightweight state management library for Clojure and ClojureScript that helps developers manage application components—like databases, servers, and caches—in a REPL-friendly way, allowing smooth reloadability of application state without losing productivity. If the whole app is one big application context (or system), cross dependencies with a solid dependency graph is an integral part of the system. But if a state is a simple top level being, these beings can coexist with each other and with other namespaces by being required instead. If a managing state library requires a whole app buy-in, where everything is a bean or a component, it is a framework, and dependency graph is usually quite large and complex, since it has everything (every piece of the application) in it. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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Your basic graph
Graph algorithms and data structures
...The tool is part of a larger library of generic graph algorithms. -
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wallaroo
C++ Dependency Injection
Wallaroo is a dependency injection library for C++. With wallaroo you can easily separate the object graph from the class implementation. You can create objects and wiring them using strings, so that you can load the "object graph" from a configuration file. -
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Haxl
Haskell library that simplifies access to remote data
Haxl is a Haskell library that simplifies access to remote data, such as databases or web-based services. Haxl can automatically batch multiple requests to the same data source, request data from multiple data sources concurrently, cache previous requests, and memoize computations. Having all this handled for you behind the scenes means that your data-fetching code can be much cleaner and clearer than it would otherwise be if it had to worry about optimizing data-fetching. To use Haxl in... -
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JavaGimmicks
Utility classes, APIs and tools for Java
A set of helper and utility classes, APIs and tools for the Java Programming Language. For more details - pleas visit the project homepage. -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. By bridging ideas from graph theory and word embedding models, this project demonstrates how graph-based machine learning can be made efficient and flexible. -
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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). -
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istiChartLib
C++ Chart Library for wxWidgets
IstiChartLib is one of the simplest c++ library for making chart or graph. It is developed using wxWidgets library. For windows, please use IstiChartLib.zip. For Linux (tested on Ubuntu) use IstiChartLib_Linux.tar.gz. For detailed documentation, please visit www.firagiel.com Password to extract: firagiel -
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Sesame
Java RDF Framework
This project is no longer actively maintained. It is succeeded by the Eclipse RDF4J project, which can be found at GitHub and at http://www.rdf4j.org/. Sesame is a de-facto standard framework for processing RDF data. This includes parsing, scalable storage, reasoning and full SPARQL 1.1 query/update support. Sesame offers a fully modular toolkit and an easy-to-use Java API that can be connected to all leading RDF storage solutions. -
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dotNetRDF is a .Net Class Library for working with RDF and SPARQL programatically built with C# 3 for the .Net Framework 3.5/4.0/Silverlight 4 and WIndows Phone 7. It provides a simple object model for representing RDF, SPARQL Queries and Updates and understands all common RDF and SPARQL syntaxes. Extensive documentation is available on the website and support is available via the mailing lists.
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Open PHIGS
PHIGS (Programmer's Hierarchical Interactive Graphics System)
...The reason for doing so is that today every graphics card manufacturer provides their own OpenGL implementation, which takes full advantage of the accelerated drawing capabilities in the hardware. PHIGS is a higher level API than OpenGL that works with a hierarchical scene graph. Models are built up in a Centralized Structure Store (CSS), a database containing the drawing primitives and their attributes (color, line style, etc.). CSSes cand be shared among a number of views, known under PHIGS as a workstation. PHIGS is defined by the ISO standards ISO/IEC 9592 & 9593. Open PHIGS provides a library for C. -
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Java implementation of Fuzzy Cognitive Maps (FCM). Implementation aims to be: small (and fast), simple to use, flexible enough to be used as a basis for other projects / libraries.
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This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.
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SPARGEL
An opensource Java graph library. Abandoned, ignore.
Spargel is a Java graph library that puts its effort in having a rather small but powerful code basis. This is achieved by extending graphs via properties in form of vertice and edge maps. Because these maps are an individual implementation depending on the graph datastructure used, they are more memory efficient than using a Java HashMap. Currently spargel is in its early stages, but will soon support more tasks.
