Search Results for "gaussian"
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Showing 165 open source projects for "gaussian"
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SuperSplat
3D Gaussian Splat Editor
SuperSplat is a free and open source tool for inspecting and editing 3D Gaussian Splats. It is built on web technologies and runs in the browser, so there's nothing to download or install. -
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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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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
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GPflow
Gaussian processes in TensorFlow
GPflow is a package for building Gaussian process models in Python. It implements modern Gaussian process inference for composable kernels and likelihoods. GPflow builds on TensorFlow 2.4+ and TensorFlow Probability for running computations, which allows fast execution on GPUs. -
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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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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution, Bayesian... -
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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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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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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment... -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels... -
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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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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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VGGSfM
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
... for dynamic scene handling, dense point cloud export, video-based reconstruction (1000+ frames), and integration with Gaussian Splatting pipelines. It leverages tools like PyCOLMAP, poselib, LightGlue, and PyTorch3D for feature matching, pose estimation, and visualization. With minimal configuration, users can process single scenes or full video sequences, apply motion masks to exclude moving objects, and train neural radiance or splatting models directly from reconstructed outputs. -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses,... -
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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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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based... -
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Chronos Forecasting
Pretrained (Language) Models for Probabilistic Time Series Forecasting
... as synthetic data generated using Gaussian processes. -
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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... -
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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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KherveFitting
Fit X-ray Photoelectron Spectroscopy (XPS) and Raman data
KherveFitting is a full featured XPS & now Raman fitting software for Windows & macOS that is simple and easy to use. KherveFitting can open Excel files (.xlsx) or import/convert .vms, .avg, .kal, .spe (Thermo, Kratos, Specs, Scienta, Omicron, Phi) files into Excel format. 5 background types available: Tougaard, Shirley, Smart, Adaptive Smart. Various peak fitting models: Product and Sum of Gaussian and Lorentzian (GL & SGL), Voigt, Asymmetric Lorentzian (LA), Doniac-Sunjic (G*DS) and many... -
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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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tools4Gaussian
Management and Analyzis of Gaussian Calculations