Search Results for "research" - Page 24
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Showing 749 open source projects for "research"
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stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course
This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1. -
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House3D
A Realistic and Rich 3D Environment
...The simulator is optimized for high-performance rendering, achieving thousands of frames per second to enable efficient large-scale training of RL agents. House3D has served as the foundation for several influential research projects such as RoomNav (for concept-based navigation) and Embodied Question Answering (EQA). -
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Deepo
Set up deep learning environment in a single command line
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment, supports almost all commonly used deep learning frameworks, supports GPU acceleration (CUDA and cuDNN included), also works in CPU-only mode, and works on Linux (CPU version/GPU version), Windows (CPU version) and OS X (CPU version). Their Dockerfile generator that allows you to customize your own environment with Lego-like modules, and automatically resolves the dependencies for you. ... -
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. -
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Training Image Operators from Samples
Tools to train Image Operators automatically from a set of samples.
TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image. -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify... -
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Neural Photo Editor
A simple interface for editing natural photos
Neural Photo Editor is an experimental machine learning application that demonstrates how generative neural networks can be used as an interactive photo editing tool. The project implements the system described in the research paper Neural Photo Editing with Introspective Adversarial Networks, which introduces a generative model capable of modifying images in semantically meaningful ways. Instead of editing images by directly manipulating pixels, the software allows users to influence changes in the latent space of a trained generative model. This approach enables large and coherent modifications to images while preserving visual realism. ... -
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TEES
Turku Event Extraction System
Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information. -
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RDRPOSTagger
A Rule-based Part-of-Speech and Morphological Tagging Toolkit
RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai... -
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Linked List Artificial Developmental System (LLADS) provides a framework for carrying out experiments and undertake development of code in the areas of evolutionary computation and artificial development.
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GT NLP Class
Course materials for Georgia Tech CS 4650 and 7650
This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models).... -
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pyclp
PyCLP is a Python library to interface ECLiPSe Constraint System
PyCLP is a Python library to interface ECLiPSe Constraint Programmig System. This module try to implement a pythonic interface to ECLiPSe ( http://www.eclipseclp.org ) by compromising on a little bit on performance. -
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SLEF
Subjective Logic Experimental Framework
Experiment developed for the paper Subjective Logic Operators in Trust Assessment: An Empirical Study by F. Cerutti, L. M. Kaplan, T. J. Norman, N. Oren, and A. Toniolo ISF Journal, 2014 -
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Distant Speech Recognition
Beamforming and Speech Recognition Toolkit
...The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and development of automatic distant speech recognition. -
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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are... -
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Gamera is a framework for the creation of structured document analysis applications by domain experts. It combines a programming library with GUI tools for the training and interactive development of recognition systems.
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ProtPOS
Prediction of PROTtein Preferred Orientation on a Surface
ProtPOS is a self-contained, lightweight, and easy-to-use software package for predicting the preferred orientation of protein on a given surface upon initial adsorption. It searches quickly for the low energy protein poses in all translational and rotational degrees of freedom of the protein with respect to the surface using particle swarm optimization. Each successful run returns the lowest energy orientation of the protein on the surface in PDB format, which is readily used for MD... -
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
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Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
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PyML is an interactive object oriented framework for machine learning written in python. PyML focuses on kernel classifiers, providing tools for feature selection, model selection, and methods for assessing classifier performance.
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Machine Learning framework in Python
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed... -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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mwetoolkit
THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/
THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/ The Multiword Expressions toolkit aids in the automatic identification and extraction of multiword units in running text. These include idioms (kick the bucket), noun compounds (cable car), phrasal verbs (take off, give up), etc. Even though it focuses on multiword expresisons, the framework is quite complete and can also be useful in any corpus-based study in computational linguistics. The mwetoolkit can be...
