Search Results for "tensor network state" - Page 6
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Showing 394 open source projects for "tensor network state"
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FLAnimatedImage
Performant animated GIF engine for iOS
FLAnimatedImage is a performant animated GIF engine for iOS. Plays multiple GIFs simultaneously with a playback speed comparable to desktop browsers. Honors variable frame delays. Behaves gracefully under memory pressure. Eliminates delays or blocking during the first playback loop. Interprets the frame delays of fast GIFs the same way modern browsers do. It's a well-tested component that powers all GIFs in Flipboard. FLAnimatedImage is a well-encapsulated drop-in component. Simply replace... -
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Open Source Shelter Manager
Operational Support for those Managing Refugee Shelters
Welcome to the Open Source Shelter Manager (OSSM). We hope this program will help you manage your shelter's data as you go about the vital task of assisting refugees. User's guide at https://www.dbaustin.com/blog/refugee-shelter-manager/users-guide/ -
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ConvNeXt
Code release for ConvNeXt model
...It achieves competitive or superior results on ImageNet and downstream datasets while being easier to deploy and train than transformers. The repository provides pretrained models, training recipes, and ablation studies demonstrating how incremental design choices collectively yield state-of-the-art performance. -
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Matrix Product State (MPS) Simulations
Numerical routines for variational matrix product state simulations.
Open Source MPS (OSMPS) is a collection of numerical routines for performing tensor network algorithms to simulate entangled, 1D many-body quantum systems. Our applications reach from ground state and excited states for statics to the dynamics of time-dependent Hamiltonians. We offer various time evolution methods with an emphasis on the support of long-range interactions through the matrix product state formalism. -
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pyTorch Tutorials
Build your neural network easy and fast
pyTorch Tutorials is an open-source collection of hands-on tutorials designed to teach developers how to build neural networks with the PyTorch framework. It covers the fundamentals of PyTorch from basic tensor operations to constructing full neural network models, making it suitable for beginners and intermediate learners alike. The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. ... -
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EarlGrey
iOS UI Automation Test Framework
EarlGrey is a native iOS UI automation test framework that enables you to write clear, concise tests. With the EarlGrey framework, you have access to enhanced synchronization features. EarlGrey automatically synchronizes with the UI, network requests, and various queues; but still allows you to manually implement customized timings, if needed. EarlGrey’s synchronization features help to ensure that the UI is in a steady state before actions are performed. This greatly increases test stability and makes tests highly repeatable. EarlGrey works in conjunction with the XCTest framework and integrates with Xcode’s Test Navigator so you can run tests directly from Xcode or the command line (using xcodebuild). ... -
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Pysces
PySCeS is the Python Simulator of Cellular Systems
PySCeS is the Python Simulator of Cellular Systems. For a network of coupled reactions it does a stoichiometric matrix analysis, calculates the time course and steady state, and does a complete control analysis. -
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Pokedex-AR
Pokedex-AR demonstrates ARCore, Sceneform, & modern Android tech stack
Pokedex-AR is a small demo application based on AR, modern Android application tech stacks, and MVVM architecture. This project focuses on ARCore and SceneForm. Also fetching data from the network and integrating persisted data from the database via repository pattern. -
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TensorNetwork
A library for easy and efficient manipulation of tensor networks
TensorNetwork is a high-level library for building and contracting tensor networks—graphical factorizations of large tensors that underpin many algorithms in physics and machine learning. It abstracts networks as nodes and edges, then compiles efficient contraction orders across multiple numeric backends so users can focus on model structure rather than index bookkeeping. Common network families (MPS/TT, PEPS, MERA, tree networks) are expressed with concise APIs that encourage experimentation and comparison. ... -
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useful-custom-react-hooks
This project was bootstrapped with Create React App
useful-custom-react-hooks is a React learning project that demonstrates a broad collection of reusable custom hooks. It is built as a Create React App project and organizes each hook into its own component example. The repository covers common UI, browser, state, timing, storage, network, and interaction patterns that React developers often rebuild across projects. It includes hooks for toggling state, debouncing values, tracking previous values, managing arrays, storing data, fetching resources, loading scripts, and reacting to browser events. It also explores more advanced use cases such as geolocation, media queries, click-outside detection, dark mode, render counting, debug information, hover behavior, and long press interactions. ... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
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Robust Video Matting (RVM)
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX
...Furthermore, we propose a novel training strategy that enforces our network on both matting and segmentation objectives. This significantly improves our model's robustness. Our method does not require any auxiliary inputs such as a trimap or a pre-captured background image, so it can be widely applied to existing human matting applications. RVM is specifically designed for robust human video matting. -
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EtherCAT Explorer
Graphical explorer for EtherCAT network
Small EtherCAT graphical Explorer in C#. Show cyclical data Allows read/write acyclic SDO Allows EEPROM read out Read slave description from it's XML file Can control the slaves state Full open source code with 2 simples master code for C# developpers. Full Java sample code for developpers. Base on Soem lib (GitHub). Npcap (with Wireshark maybe) should be installed before in Winpcap compatible mode : don't miss the check box ! EtherCAT™ is a registered trademark of Beckhoff... -
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OpenTSDB
A scalable, distributed time series database
...Interaction with OpenTSDB is primarily achieved by running one or more of the TSDs. Each TSD is independent. There is no master, no shared state so you can run as many TSDs as required to handle any load you throw at it. Each TSD uses the open-source database HBase or hosted Google Bigtable service to store and retrieve time-series data. -
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Osmoseit.NExGen
La plateforme de dématérialisation de nouvelle génération. - BWS
Plateforme technologique générique pour la dématérialisation des processus administratifs et de gestion reposant sur le dernier état de l'art technologique. Le projet BWS consiste à développer la solution de gestion de portail communautaire. Generic technological platform for the dematerialization of administrative and management processes based on the latest state of the art technology. The BWS project is to develop the community portal management solution. -
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Hyperledger Burrow
A permissioned Ethereum smart-contract blockchain node
...Burrow runs Ethereum Virtual Machine (EVM) and Web Assembly (WASM) smart contracts. Burrow networks are synchronized using the Tendermint consensus algorithm. A node can detect if its state is corrupted or if a validator is dishonestly executing the protocol. Run a private or public permissioned network. Stakeholders may vote for autonomous smart contract upgrades. Application state is organised in an event stream and can drive external systems. -
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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. ... -
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Maggy is a tool for designing an application around a Sqlite or a MySQL database. Oriented towards information databases, its main task is searching information quickly through lists and inverted data. Originally written in php and designed for MySQL, the version 2 is a full rewrite in Python, now oriented to SQLite. MySQL support may be included, but not fully implemented yet. Maggy2 is in beta state and the documentation is missing. But the program is quite fully functional.
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CapsGNN
A PyTorch implementation of "Capsule Graph Neural Network"
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019). The high-quality node embeddings learned from the Graph Neural Networks (GNNs) have been applied to a wide range of node-based applications and some of them have achieved state-of-the-art (SOTA) performance. However, when applying node embeddings learned from GNNs to generate graph embeddings, the scalar node representation may not suffice to preserve the node/graph properties efficiently, resulting in sub-optimal graph embeddings. ... -
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YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
This is a ROS package developed for object detection in camera images. You only look once (YOLO) is a state-of-the-art, real-time object detection system. In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and Ubuntu 20.04. ... -
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BarcodeScanner
A simple and beautiful barcode scanner
BarcodeScanner is a simple and beautiful wrapper around the camera with barcode-capturing functionality and a great user experience. To start capturing just instantiate BarcodeScannerViewController, set the needed delegates and present it. While the user sees a nice loading animation you can perform some background task, for example, make a network request to fetch product info based on the code. When the task is done you have 3 options to proceed. We styled BarcodeScanner to make it look... -
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
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Simulation on energy management of an uneven clustered EH-WSNs by cooperative q-learning Power management in wireless sensor networks (WSNs) is very important due to the limited energy of batteries. Sensor nodes with harvesters can extract energy from environmental sources as supplemental energy to break this limitation. In a clustered solar-powered sensor network where nodes in the network are grouped into clusters, data collected by cluster members are sent to their cluster head and finally transmitted to the base station. The goal of the whole network is to maintain an energy neutrality state and to maximize the effective data throughput of the network. The cooperative Q-learning is applied in this multi-agent environment the solar-powered wireless sensor networks to keep harvested energy more balanced among the whole clustered network.
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. ...
