Search Results for "research" - Page 7
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Showing 426 open source projects for "research"
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
...Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. It includes training scripts, evaluation code, and pre-trained models that achieve strong results on popular benchmarks such as AFW, PASCAL Face, FDDB, and WIDER FACE. The framework is optimized for speed and accuracy, making it suitable for both academic research and practical applications in computer vision. -
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Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more... -
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. ... -
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fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and trading. Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way. -
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DistAlgo
A Language for Distributed Algorithms
DistAlgo is a very high-level language for expressing distributed algorithms. -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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PyEdit Editor
Configurable Editor in Python
PyEdit is a fully featured fast text editor written in Python. It can be used in any platform that has GTK. Because it is written in Python, it is easily configurable. Features code spell check and macro recording. Tested in Win/Lin/Mac --- Update: Using the editor full time V23 is mature enough for production --- Update: Had to downgrade to PyGTK 2.22.xx as 2,24,x had a double click message bug. (uploaded 22.2 to this project) --- Update: V33 is working as a champ. New... -
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Python/xarray tutorial
Python/xarray tutorial for GEOS-Chem users
If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. -
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Madara
Middleware for distributed applications
The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system... -
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GDL - GNU Data Language, a free IDL (Interactive Data Language, see http://ittvis.com/idl/) compatible incremental compiler.
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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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IPS Framework
A simple Python framework for loosely-coupled multiphysics simulations
The IPS Framework has migrated to https://github.com/HPC-SimTools/IPS-framework The IPS framework was developed to support loosely-coupled integrated modeling of fusion plasmas (and was originally the Integrated Plasma Simulator). However, the design is quite general, and is suitable for many scientific and engineering domains. In addition to plasma physics, it is also being used in the engineering of batteries. One of the novel features of the IPS framework is its... -
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That project aims at providing a clean API, and the corresponding C++ implementation, for the basis of Airline IT Business Object Model (BOM), ie, to be used by several other Open Source projects, such as RMOL, Air-Sched, Travel-CCM, OpenTREP, etc.
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CIGI Compliance Tools
Tools for Testing IG CIGI Compliance
Tools for testing CIGI IG and host implementations against the CIGI standard. -
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Simple Python Fixed-Point Module
Pure-python binary fixed-point arithmetic library
This Python module provides basic facilities for mathematics on fixed-point numbers. The number of fractional binary digits is tunable, allowing near-arbitrary precision arithmetic. Arithmetic & functions such as sqrt, exp, log, sin & cos are available. For the latest releases please visit https://github.com/rwpenney/spfpm -
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pyparsing is a general parsing module for Python. Grammars are implemented directly in the client code using parsing objects, instead of externally, as with lex/yacc-type tools. Includes simple examples for parsing SQL, CORBA IDL, and 4-function math
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Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...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. 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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PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
...The library’s design emphasizes flexibility and modularity, supporting advanced features like default scopes, parameter templates, and variable reuse. It also allows easy integration with custom operations and third-party libraries, making it ideal for both research experimentation and production-grade modeling. By combining TensorFlow’s power with an intuitive builder-style API, Pretty Tensor accelerates model development without sacrificing transparency or control. -
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CMake BASIS
Build system And Software Implementation Standard
The CMake Build system And Software Implementation Standard makes it easy to create sharable software and libraries that work together. This is accomplished by combining and documenting some of the best practices and utilities available. More importantly, BASIS supplies a fully integrated suite of functionality to make the whole process seamless! Check out the web site for more information. The Git repository of this project is hosted on GitHub. Some interesting facts about this project... -
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AirTSP
Simulated Airline Travel Solution Provider Library
AirTSP is also named AirTSP (TSP standing for Travel Service Provider). That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline Schedule Management System. It is intended to be used in simulated environments only: it is not designed to work in the real-world of Airline IT operations. AirTSP/AirTSP makes an extensive use of existing open-source libraries for increased functionality, speed and accuracy. In particular the Boost (C++... -
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mds-utils
General purpose utilities for C++ and Python developers
This library is intended to become a collection of several C++ utilities. At present it contains: 1. a tool for detecting machine endianity. 2. utilities for the Boost uBLAS library. Amongst them, some type traits for detecting different uBLAS matrix types. 3. some useful classes that allow to treat the old C FILE pointer as a C++ stream. 4. C++ wrappers of the main Python objects, independent of those in Boost Python. Wrappers are provided also for NumPy arrays. 5. C++...
