Search Results for "probabilistic neural network"
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Showing 32 open source projects for "probabilistic neural network"
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function... -
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NNlib.jl
Neural Network primitives with multiple backends
This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently. -
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GraphNeuralNetworks.jl
Graph Neural Networks in Julia
GraphNeuralNetworks.jl is a graph neural network library written in Julia and based on the deep learning framework Flux.jl. -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit... -
The progression to modern application stacks and microservices architectures has resulted in orders of magnitude more logs, metrics, events, and traces. Like gravity, data attracts more data, making it increasingly difficult to move and process as it accumulates over time. More than ever, there is a need to be able to stream-process, filter, mask, transform, aggregate, analyze, and route that data to various data tier destinations optimized for specific usage.
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PyTorch Forecasting
Time series forecasting with PyTorch
... with logging in tensorboard and generic visualizations such actual vs predictions and dependency plots. Multiple neural network architectures for timeseries forecasting that have been enhanced for real-world deployment and come with in-built interpretation capabilities. The package is built on PyTorch Lightning to allow training on CPUs, single and multiple GPUs out-of-the-box. -
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Kinetic.jl
Universal modeling and simulation of fluid mechanics upon ML
Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs. -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in doubt... -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
BackBox seamlessly integrates with network monitoring and NetOps platforms and automates configuration backups, restores, and change detection. BackBox also provides before and after config diffs for change management, and automated remediation of discovered network security issues.
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Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a... -
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to... -
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OYSTER Entity Resolution
OYSTER is an Entity Resolution engine
Entity Resolution is the process by which a dataset is processed and records are identified that represent the same real-world entity. OYSTER (Open sYSTem Entity Resolution) is an entity resolution system that supports probabilistic direct matching, transitive linking, and asserted linking. To facilitate prospecting for match candidates (blocking), the system builds and maintains an in-memory index of attribute values to identities. Because OYSTER has an identity management system, it also... -
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DSTK - Data Science TooKit 3
Data and Text Mining Software for Everyone
DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI... -
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DeepLearningProject
An in-depth machine learning tutorial
This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. The dataset is not one of the standard sets like MNIST or CIFAR, you... -
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OpenANN
Basic Artificial Neural Network
OpenANN is a basic artificial neural network toolset. It is not being actively maintained. For performance neural networking, consider an alternative (such as https://sourceforge.net/projects/openann-project or https://www.tensorflow.org) -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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optPBN
An optimization toolbox for probabilistic Boolean networks
We introduce optPBN, a Matlab-based toolbox for the optimization of probabilistic Boolean networks (PBN) which operates under the framework of the BN/PBN toolbox from Shmulevich et al. optPBN offers an easy generation of probabilistic Boolean networks from Boolean rule-based modeling and allows for flexible measurement data integration from multiple experiments and a subsequent integrated optimization problem generation which then can be solved with different optimizers. Thereby optPBN allows... -
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neural network designer
a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...
This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you... -
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XNBC: neurobiology simulation tool
XNBC is a graphic application to simulate biologic neural networks.
XNBC is a full featured application for computer naive neuroscientists. It simulates biological neural networks using graphic tools to edit neurons and networks, to run the simulation and to analyze results. Written in C, it runs on Unix and Windows. Web site : http://ticemed-sa.upmc.fr/xnbc/ All recent versions are on this site. -
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YaaCs - Yet Another Advanced Cati system
survey research software integrate for CATI/ CAWI/ CAMI survey
YaaCs, developed by Demetra www.opinioni.net, survey research via phone CATI (also Voip) and web CAWI and for telemarketing. Develop questionnaire for survey, create probabilistic sample, monitoring Interviewer, export survey data in statistical.. It's integrate with www.modsurvey.org. Sviluppato da Demetra www.opinioni.net per indagini CATI/ CAWI e CAMI. Vi permette di programmare dei questionari elettronici, campionamenti, monitorare gli intervistatori, esportare dati in formati... -
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imDEV
Tools for multivariate data visualization, exploration and analysis.
You may also like some newer work: http://createdatasol.com/ Project imDEV is an application of RExcel, which seamlessly integrates Excel and R for tasks focused on multivariate data visualization, exploration, and analysis. Interactive modules for dimensional reduction (imPCA), prediction (imPLS), feature selection, analysis of correlation (imCorrelations) and generation of networked structures (imGraph) provide an integrated environment for systems level analysis of multivariate data. -
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QTrader is a stock and commodity analysis software designed in C#. It will assist with analysis of the various financial markets and provide a visual medium to assist in making decisions. QTrader will be designed to integrate with MT4 and MT5. Some of the features planned for QTrader: - Artificial Neural Networks for pattern recognition - Find stock trades based on leading criteria for stock market trades - Automatic loading of stock data from live sources - Ability to connect...
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detect human presence Uses artificial neural network Complete netbeans project No need to train Just start to use it as u like!
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Tool for visualizing artificial neural networks in Matlab using the Matlab Neural Network Toolbox (see wiki for details).
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PlexBench is a cross-platform, web-enabled, analysis tool that is driven by a scalable backpropagation feed-forward neural network. It uses embedded Perl for scripting and is written in the style of an in-process Component Object Model (COM) C++ program.