Showing 147 open source projects for "data structure"

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    TenorSpace.js

    TenorSpace.js

    Neural network 3D visualization framework

    ...TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. TensorSpace is a neural network 3D visualization framework designed for not only showing the basic model structure but also presenting the processes of internal feature abstractions, intermediate data manipulations and final inference generations. ...
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  • 2
    Generative Models

    Generative Models

    Collection of generative models, e.g. GAN, VAE in Pytorch

    This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch...
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  • 3
    ZPar statistical parser. Universal language support (depending on the availability of training data), with language-specific features for Chinese and English. Currently support word segmentation, POS tagging, dependency and phrase-structure parsing.
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  • 4

    JCLTP

    A Java Class Library for Text Processing

    JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types...
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  • 5
    node-opencv

    node-opencv

    OpenCV Bindings for node.js

    OpenCV bindings for Node.js. OpenCV is the defacto computer vision library - by interfacing with it natively in node, we get powerful real time vision in js. People are using node-opencv to fly control quadrocoptors, detect faces from webcam images and annotate video streams. If you're using it for something cool, I'd love to hear about it! You'll need OpenCV 2.3.1 or newer installed before installing node-opencv. You can use opencv to read in image files. Supported formats are in the OpenCV...
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  • 6

    WebDjVuTextEd

    Edit the OCR text layer of DjVu documents in a web browser

    WebDjVuTextEd allows to edit the text layer of OCR'ed DjVu documents in a web browser. You can modify the structure (paragraphs, lines, words...) create, delete, edit text nodes, modify their container box by mouse, and run a spellchecker. The program does not directly read the DjVu files, it requires exported XML text data and images. When using without a webserver, you can open and save local files, but cannot take advantages of auto-save and spell checking.
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  • 7

    JAABA

    The Janelia Automated Animal Behavior Annotator

    The Janelia Automatic Animal Behavior Annotator (JAABA) is a machine learning-based system that enables researchers to automatically compute interpretable, quantitative statistics describing video of behaving animals. Through our system, users encode their intuition about the structure of behavior by labeling the behavior of the animal, e.g. walking, grooming, or following, in a small set of video frames. JAABA uses machine learning techniques to convert these manual labels into behavior detectors that can then be used to automatically classify the behaviors of animals in large data sets with high throughput. ...
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  • 8

    Chordalysis

    Log-linear analysis (data modelling) for high-dimensional data

    ...However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures, also known as chordal graphs. Chordalysis makes it possible to discover the structure of datasets with thousands of variables on a standard desktop computer. Associated papers at ICDM 2013, ICDM 2014 and SDM 2015 can be found at http://www.francois-petitjean.com/Research/ YourKit is supporting Chordalysis open source project with its full-featured Java Profiler. ...
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  • 9
    S-Match

    S-Match

    S-Match is a semantic matching framework.

    S-Match is a semantic matching framework. S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another. S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. S-Match applies as a solution in many fields, including: information integration,...
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  • 10

    StabLe

    An algorithm for learning stable graphical models from data

    Stable Graphical Model Learning (StabLe) is an algorithm for learning the structure and parameters of stable graphical (SG) models from data. Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon. SG models are multi-variate stable distributions that represent Bayesian networks whose edges encode linear dependencies amongst random variables. ...
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  • 11

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A.
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  • 12

    drvq

    dimensionality-recursive vector quantization

    drvq is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. ...
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  • 13
    Unsupervised TXT classifier

    Unsupervised TXT classifier

    Classify any two TXT documents, no training required - JAVA

    ...This extracts a relevant structure for both documents (and thus avoids the over-training) which are then compared using the Vector-Space analysis to give a range of belonging of one document to another (and thus avoids the shortage of information). This method can be used to create the user-defined classes by merging texts of certain categories and then to calculate the relevant distances between the documents, but this is not necessary.
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  • 14
    NOTE: This project was moved to: https://github.com/eetorres The BPANNA is a flexible Back propagation neural network, which include the Conjugate Gradient and the Levenberg-Marquardt. You can change the number of inputs, number of layers, number of neurons per layer and outputs. It included an structure editor.
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  • 15

    AdPreqFr4SL

    Adaptive Prequential Learning Framework

    The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. The method for handling concept drift is based on the Shewhart P-Chart. ...
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  • 16

    FreeFuzzyTime

    It's a time reasoner that can be integrated in medical applications.

    FuzzyTime module is a time reasoner base on Fuzzy Temporal Constraint Networks (FTCN) which treats fuzzy temporal information efficiently. It can be integrated into applications for diagnosis. This is especially important in areas like Intesive Care Units where patients' data are handled by a temporal data base. The FuzzyTime module is a structure which consists of three levels of abstraction. The upper layer is the user interface where a translator transforms the expressions introduced by the user into temporal relations between temporal entities (points and intervals). The semantic of user’s expressions is analized and stored in the intermediate layer or temporal world. ...
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  • 17
    A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
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  • 18
    Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.
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  • 19
    Random Projection Trees is a recursive space partitioning datastructure which can automatically adapt to the underlying (linear or non-linear) structure in data. It has strong theoretical guarantees on rates of convergence and works well in practice.
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  • 20
    a C++ template container implementation of k-dimensional space sorting based on the kd-tree data structure. THIS PROJECT HAS MOVED TO ALIOTH.DEBIAN.ORG
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  • 21
    MatLab Methods for Quantifying the Informational Structure of Sensory and Motor Data
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  • 22
    GiveASens is a Semantic Web project that aims to provide a web tool, user friendly, to edit structured data following ontology structures. The application might be able to build an interface according to the model structure and adapt to any new model.
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