Search Results for "gaussian"
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Showing 150 open source projects for "gaussian"
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Yooz provides the smartest, most powerful, and easiest-to-use cloud-based E-invoicing and Purchase-to-Pay automation solution. It delivers unmatched savings, speed, and security with affordable zero-risk subscriptions to more than 5,000 customers and 300,000 users worldwide.
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SafetyIQ is revolutionizing the way businesses approach safety. As a leading provider of comprehensive workplace safety software, we cater to four key areas: Mobile Worker Safety, EHS (Environment, Health, and Safety), Fatigue Management, and Training. Our platform is designed to safeguard your workers, no matter their location or task, ensuring all-around safety compliance. Unlike most safety software providers that only react to incidents or implement proactive measures, SafetyIQ introduces a third pillar to safety management - predictive analytics. We transform the untapped wealth of safety data within your organization into actionable insights to inform safety strategies, mitigating risks even before they aris
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PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable... -
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AbstractGPs.jl
Abstract types and methods for Gaussian Processes
AbstractGPs.jl is a package that defines a low-level API for working with Gaussian processes (GPs), and basic functionality for working with them in the simplest cases. As such it is aimed more at developers and researchers who are interested in using it as a building block than end-users of GPs. You may want to go through the main API design documentation. -
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AugmentedGaussianProcesses.jl
Gaussian Process package based on data augmentation, and sparsity
AugmentedGaussianProcesses.jl is a Julia package in development for Data Augmented Sparse Gaussian Processes. It contains a collection of models for different gaussian and non-gaussian likelihoods, which are transformed via data augmentation into conditionally conjugate likelihood allowing for extremely fast inference via block coordinate updates. There are also more options to use more traditional variational inference via quadrature or Monte Carlo integration. -
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Caesar.jl
Robust robotic localization and mapping
A multimodal/non-Gaussian robotic toolkit for localization and mapping -- reducing the barrier of entry for sensor/data fusion tasks, including Simultaneous Localization and Mapping (SLAM). Code changes are currently tracked via Github's integrated Milestone/Issues/PR system. -
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FastGaussQuadrature.jl
Julia package for Gaussian quadrature
A Julia package to compute n-point Gauss quadrature nodes and weights to 16-digit accuracy and in O(n) time. So far the package includes gausschebyshev(), gausslegendre(), gaussjacobi(), gaussradau(), gausslobatto(), gausslaguerre(), and gausshermite(). This package is heavily influenced by Chebfun. -
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QuadGK.jl
adaptive 1d numerical Gauss–Kronrod integration in Julia
This package provides support for one-dimensional numerical integration in Julia using adaptive Gauss-Kronrod quadrature. The code was originally part of Base Julia. It supports the integration of arbitrary numeric types, including arbitrary-precision (BigFloat), and even the integration of arbitrary normed vector spaces. The package provides three basic functions: quadgk, gauss, and kronrod. quadgk performs the integration, gauss computes Gaussian quadrature points and weights for integrating... -
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Copulas
A library to model multivariate data using copulas
Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table of numerical data, use Copulas to learn the distribution and generate new synthetic data following the same statistical properties. Choose from a variety of univariate distributions and copulas – including Archimedian Copulas, Gaussian Copulas and Vine Copulas. Compare real and synthetic data visually after building your model. Visualizations are available as 1D... -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic... -
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PDMats.jl
Uniform Interface for positive definite matrices of various structures
Uniform interface for positive definite matrices of various structures. Positive definite matrices are widely used in machine learning and probabilistic modeling, especially in applications related to graph analysis and Gaussian models. It is not uncommon that positive definite matrices used in practice have special structures (e.g. diagonal), which can be exploited to accelerate computation. PDMats.jl supports efficient computation on positive definite matrices of various structures... -
Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers.
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EvoTrees.jl
Boosted trees in Julia
A Julia implementation of boosted trees with CPU and GPU support. Efficient histogram-based algorithms with support for multiple loss functions, including various regressions, multi-classification and Gaussian max likelihood. -
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AtomAI
Deep and Machine Learning for Microscopy
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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Jmol
An interactive viewer for three-dimensional chemical structures.
Over 1,000,000 page views per month. Jmol/JSmol is a molecular viewer for 3D chemical structures that runs in four independent modes: an HTML5-only web application utilizing jQuery, a Java applet, a stand-alone Java program (Jmol.jar), and a "headless" server-side component (JmolData.jar). Jmol can read many file types, including PDB, CIF, SDF, MOL, PyMOL PSE files, and Spartan files, as well as output from Gaussian, GAMESS, MOPAC, VASP, CRYSTAL, CASTEP, QuantumEspresso, VMD, and many other... -
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NLIGA
Open source Matlab code for nonlinear isogeometric analysis
A unified framework, NLIGA (Non-Linear Isogeometric Analysis), is developed for mainly solving two and three-dimensional nonlinear problems on the MATLAB platform by using isogeometric analysis (IGA). Nonlinear hyperelastic and elastoplastic materials are primarily considered at this stage. Newton-Raphson method is used to solve the nonlinear governing equations. A series of benchmark examples are performed to validate the procedures. The visualization procedures are also developed to... -
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expopt
Set of tools for manipulations with ANO basis sets
Expopt: the program is intended for optimizing primitive gaussian functions for basis sets -
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Image16
Image viewer/editor specialized in astrophotography 16bits processing
Opens/saves TIF, FITS, PNG, XISF, PXM, RAW, JPG, XCF, PSD. AsinH, Sqrt, Ln, Exp and Sqr stretching, HSL and RGB adjusting, Levels and Curves adjusting and Background Extraction for Color Balance, Flatness and Gradient Correction. Arithmetic between images. Resizing and croping. Color Balance based on background, selection or stars B-V (after platesolving). Debayering/Bayering. Inversion, mirroring, rotation, barrel/pincushion correction. RGB alignment/shifting. Erode, Dilate, ... Blurring... -
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STK
a Small (Matlab/Octave) Toolbox for Kriging
The STK is a (not so) Small Toolbox for Kriging. Its primary focus in on the interpolation / regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior. The STK also provides tools for the sequential and non-sequential design of experiments. Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE... -
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trilat-umn
Using FRET distances to trilaterate the location of a FRET acceptor
This software performs trilateration using an arbitrary number of donor sites and FRET distances with the aim to locate the position of a FRET acceptor in a protein structure. Our trilateration approach takes into account Gaussian distance distributions as fitted to the FLT-FRET measurement for each donor position. The normalized sum of the distance distributions from all of the donor sites to one acceptor is generated as a probability map describing the acceptor’s location. This volumetric map... -
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The attached files contain software developed for the simulation of pulsed EPR and ENDOR spectra of Gd(III) spin labels, including ENDOR spectra. The results obtained using this software are published at https://doi.org/10.26434/chemrxiv-2023-hg5zc The folder "Simulations.zip" contains all final simulation files used in this work
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FUNseq
Cell segmentation/tracking for determing aggresive cancer phenotypes
This page shows the cell segmentation/tracking program for FUNseq pipeline. Identifying a sparse subset of cancer cells from a large heterogeneous population, based on aggressive phenotypes (like invasive migration, multipolar divisions, or asymmetric lineage development) is challenging. Also, such aberration identification is critical, as cells exhibiting these characteristics are linearly correlated with poor prognosis. A high-throughput screening microscope has been developed in our... -
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jfPaint
Multi-Tabbed and Multi-Layered Paint program with a rich tool set.
Multi-Tabbed and Multi-Layered Paint program with a rich tool set. Features : pencil, line, curve, fill, box, circle, text, substitute, transparency, gradients and gaussian blur. Supports : JPG, PNG, BMP, TIFF, SVG, multi-layer proprietary file format (.jfpaint) -
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Argo
ARGO is a program for analysis of electronic structure calculations
The `Argo' program draws its name from ancient Greek, referencing the vessel of the same name commissioned for Jason's renowned Argonauts expedition. This choice symbolizes the pursuit of making the best use of quantum chemical calculation results. ARGO facilitates the analysis of results obtained from quantum chemistry codes, specifically Gaussian. This task is achieved through a set of Python scripts. Our code is freely available throughout the academic community with the ambition to be used... -
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SAGECAL
GPU/MIC accelerated radio interferometric calibration program
SAGECal is a very fast, memory efficient and GPU accelerated radio interferometric calibration program. It can handle all source models including points, Gaussians and Shapelets. It can calibrate along hundreds of directions without running out of memory in almost real time. Intel Xeon Phi acceleration is also available. Distributed calibration using MPI and consensus optimization is enabled. Also tools to build/restore sky models are included. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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tools4Gaussian
Management and Analyzis of Gaussian Calculations