Search Results for "research" - Page 21
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Showing 748 open source projects for "research"
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tensorflow_template_application
TensorFlow template application for deep learning
tensorflow_template_application is a template project that demonstrates how to structure scalable applications built with TensorFlow. The repository provides a standardized architecture that helps developers organize machine learning code into clear components such as data processing, model training, evaluation, and deployment. Instead of focusing on a specific algorithm, the project emphasizes software engineering practices that make machine learning systems easier to maintain and extend.... -
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jiant
jiant is an nlp toolkit
Jiant is a multitask NLP framework for fine-tuning transformer-based models on multiple natural language understanding (NLU) tasks. -
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DrQA
Reading Wikipedia to Answer Open-Domain Questions
...The repository includes scripts to build the Wikipedia index, train the reader, and evaluate end-to-end performance. DrQA popularized a practical recipe for combining IR and neural reading, and it remains a strong baseline for open-domain QA research and production prototypes. -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. ... -
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Awesome Community Detection Research
A curated list of community detection research papers
A collection of community detection papers. A curated list of community detection research papers with implementations. Similar collections about graph classification, classification/regression tree, fraud detection, and gradient boosting papers with implementations. -
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DeepSpeech
Open source embedded speech-to-text engine
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page. -
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
...It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. Task driven implementation with dynamic model and dataset resolution from arguments. Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. ... -
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MLOps Course
Learn how to design, develop, deploy and iterate on ML apps
The MLOps Course by Goku Mohandas is an open-source curriculum that teaches how to combine machine learning with solid software engineering to build production-grade ML applications. It is structured around the full lifecycle: data pipelines, modeling, experiment tracking, deployment, testing, monitoring, and iteration. The repository itself contains configuration, code examples, and links to accompanying lessons hosted on the Made With ML site, which provide detailed narrative explanations... -
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Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection,... -
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Ad-papers
Papers on Computational Advertising
...These papers represent key developments in large-scale industrial machine learning systems used by digital advertising platforms. The repository categorizes papers by topic and provides links to research publications, allowing readers to easily explore the evolution of machine learning techniques in advertising and recommendation domains. Many of the included papers originate from major technology companies and research institutions that have contributed foundational work in applied machine learning systems. -
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Synonyms
Chinese synonyms, chat robot, intelligent question and answer toolkit
..."Synonyms Cilin" was compiled by Mei Jiaju and others in 1983, and now widely used is "Synonyms Cilin Extended Edition" maintained by the Social Computing and Information Retrieval Research Center of Harbin Institute of Technology. Classes and subclasses, sort out the relationship between words, the extended version of the synonym word forest contains more than 70,000 words, of which more than 30,000 words are shared in the form of open data. -
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Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
...While the repository is archived and provided as-is, it remains a valuable starting point for experimenting with autoregressive transformers applied directly to raw pixel data. By demonstrating GPT’s flexibility across modalities, Image-GPT influenced subsequent multimodal generative research. -
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FixRes
Reproduces results of "Fixing the train-test resolution discrepancy"
FixRes is a lightweight yet powerful training methodology for convolutional neural networks (CNNs) that addresses the common train-test resolution discrepancy problem in image classification. Developed by Facebook Research, FixRes improves model generalization by adjusting training and evaluation procedures to better align input resolutions used during different phases. The approach is simple but highly effective, requiring no architectural modifications and working across diverse CNN backbones such as ResNet, ResNeXt, PNASNet, and EfficientNet. FixRes demonstrates that a mismatch between training and testing resolutions often leads to suboptimal accuracy, and fine-tuning the classifier and batch normalization layers at higher test resolutions significantly enhances performance. ... -
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ALAE
Adversarial Latent Autoencoders
ALAE (Adversarial Latent Autoencoders) is a deep learning research implementation that combines autoencoders with generative adversarial networks to produce high-quality image synthesis models. The project implements the architecture introduced in the CVPR research paper on Adversarial Latent Autoencoders, which focuses on improving generative modeling by learning latent representations aligned with adversarial training objectives. -
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TextBrewer
A PyTorch-based knowledge distillation toolkit
TextBrewer is a PyTorch-based model distillation toolkit for natural language processing. It includes various distillation techniques from both NLP and CV field and provides an easy-to-use distillation framework, which allows users to quickly experiment with the state-of-the-art distillation methods to compress the model with a relatively small sacrifice in the performance, increasing the inference speed and reducing the memory usage. -
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OpenAI Glow
Copy code in "Glow: Generative Flow with Invertible 1x1 Convolutions"
...Glow’s architecture is based on reversible layers and efficient flow operations, which allow large-scale training while keeping memory usage manageable. The repository provides training code, pretrained models, and scripts for generating samples or reproducing key results from the original research. Glow is primarily intended for researchers and practitioners exploring generative modeling, likelihood-based training, and interpretable deep learning systems. -
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PyArmadillo
linear algebra library for Python
PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma -
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Multi-Agent Emergence Environments
Environment generation code for the paper "Emergent Tool Use"
multi-agent-emergence-environments is an open source research environment framework developed by OpenAI for the study of emergent behaviors in multi-agent systems. It was designed for the experiments described in the paper and blog post “Emergent Tool Use from Multi-Agent Autocurricula”, which investigated how complex cooperative and competitive behaviors can evolve through self-play. The repository provides environment generation code that builds on the mujoco-worldgen package, enabling dynamic creation of simulated physical environments. ... -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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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. NLP Architect is a model-oriented library designed to showcase novel and different neural network optimizations. The library contains NLP/NLU-related models per task, different neural network topologies (which are used in models), procedures for simplifying workflows in the library, pre-defined data processors and dataset loaders and misc utilities. ... -
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Neural Networks Collection
Neural Networks Collection
This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
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surpriver
Find big moving stocks before they move using machine learning
...The framework includes modules for retrieving market data, computing technical indicators, and applying anomaly detection algorithms to identify unusual patterns. The project is intended as a research tool for quantitative finance experiments and algorithmic trading strategy development. -
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Consistent Depth
We estimate dense, flicker-free, geometrically consistent depth
Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. -
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VideoPose3D
Efficient 3D human pose estimation in video using 2D keypoint
...The framework includes pretrained models, data preprocessing utilities, visualization tools, and evaluation scripts for standard benchmarks like Human3.6M. VideoPose3D has been used widely in computer vision research for human motion understanding, activity recognition, and animation generation. -
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GluonNLP
NLP made easy
...Here are examples to evaluate the pre-trained embeddings included in the Gluon NLP toolkit as well as example scripts for training embeddings on custom datasets. Fasttext models trained with the library of Facebook research are exported both in text and a binary format. Unlike the text format, the binary format preserves information about subword units and consequently supports the computation of word vectors for words unknown during training (and not included in the text format). Besides training new fastText embeddings with Gluon NLP it is also possible to load the binary format into a Block provided by the Gluon NLP toolkit.
