Search Results for "monte carlo"
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Showing 200 open source projects for "monte carlo"
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Yeastar: Business Phone System and Unified CommunicationsUser-friendly, optimized, and scalable, the Yeastar P-Series Phone System redefines business connectivity by bringing together calling, meetings, omnichannel messaging, and integrations in one simple platform—removing the limitations of distance, platforms, and systems.
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QuasiMonteCarlo.jl
Lightweight and easy generation of quasi-Monte Carlo sequences
Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML). This is a lightweight package for generating Quasi-Monte Carlo (QMC) samples using various different methods. -
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Monte Carlo eXtreme (MCX)
Physically accurate and validated GPU ray-tracer
MCX is a GPU-accelerated, general-purpose, physically-accurate and feature-rich 3-D light transport simulator. It is one of the fastest simulators because it can use tens of thousands of GPU threads to simulate photons in parallel.">
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EMC: Enhanced Monte Carlo; A multi-purpose modular and easy extendable solution to molecular and mesoscale simulations
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Mctx
Monte Carlo tree search in JAX
mctx is a Monte Carlo Tree Search (MCTS) library developed by Google DeepMind for reinforcement learning research. It enables efficient and flexible implementation of MCTS algorithms, including those used in AlphaZero and MuZero. -
Ditto Edge Server is a lightweight standalone server for resource-constrained edge environments, based on the core Ditto Edge SDK.Ditto's Edge SDK is the only thing your edge devices need to ensure your application is operational in any environment, regardless of network conditions.
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DynamicHMC
Implementation of robust dynamic Hamiltonian Monte Carlo methods
Implementation of robust dynamic Hamiltonian Monte Carlo methods in Julia. In contrast to frameworks that utilize a directed acyclic graph to build a posterior for a Bayesian model from small components, this package requires that you code a log-density function of the posterior in Julia. Derivatives can be provided manually, or using automatic differentiation. Consequently, this package requires that the user is comfortable with the basics of the theory of Bayesian inference, to the extent of coding a (log) posterior density in Julia. ... -
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Prophylactic-replacement-of-voice-prosthesis---Suppl-Monte-Carlo-simulations
Monte-Carlo simulations for: Prediction of prophylactic replacement of voice prosthesis in laryngectomized patients – A retrospective cohort study
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Gen.jl
A general-purpose probabilistic programming system
...Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language for writing down generative models, inference models, variational families, and proposal distributions using ordinary code. But it also lets users migrate parts of their model or inference algorithm to specialized modeling languages for which it can generate especially fast code. ... -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
...TFP is open source and available on GitHub. Tools to build deep probabilistic models, including probabilistic layers and a `JointDistribution` abstraction. Variational inference and Markov chain Monte Carlo. A wide selection of probability distributions and bijectors. Optimizers such as Nelder-Mead, BFGS, and SGLD. -
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Integrals.jl
A common interface for quadrature and numerical integration
Integrals.jl is an instantiation of the SciML common IntegralProblem interface for the common numerical integration packages of Julia, including both those based upon quadrature as well as Monte-Carlo approaches. By using Integrals.jl, you get a single predictable interface where many of the arguments are standardized throughout the various integrator libraries. This can be useful for benchmarking or for library implementations since libraries that internally use a quadrature can easily accept an integration method as an argument. -
Smarter Packing Decisions for Retailers and 3PLsPaccurate is the only patented cartonization solution that optimizes for transportation costs directly. So you can have the right boxes, and control how they're packed.
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used... -
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Meridian
Meridian is an MMM framework
...The framework provides a robust foundation for constructing in-house MMM pipelines capable of handling both national and geo-level data, with built-in support for calibration using experimental data or prior knowledge. Meridian uses the No-U-Turn Sampler (NUTS) for Markov Chain Monte Carlo (MCMC) sampling to produce statistically rigorous results, and it includes GPU acceleration to significantly reduce computation time. -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
...The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift. -
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RMCProfile
Big box modeling for total scattering via the Reverse Monte Carlo
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ntuacarlo
A open-source implementation library of optimization algorithms
ntuacarlo: library of open-source implementation of optimization algorithms for Matlab/GNU Octave The library implements matlab functions for the following optimization algorithms: Simulated Annealing Particle Swarm Optimization Monte Carlo Exhaustive search The signature of the functions follow the same as the ga() function of Matlab. All the functions support lower and upper bounds, linear and non-linear constraints, and integer variables.Octave -
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JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.
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oxDNA
A code primarily aimed at DNA and RNA coarse-grained simulations
The oxDNA code has been moved to https://github.com/lorenzo-rovigatti/oxDNA, please go there for new releases. -
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eavref
A tool for low-power CMOS voltage reference designs
EAVREF is a computer-aided tool for robustly designing ultra-low-power CMOS voltage references. The tool is compatible with the powerful Ngspice simulator, enabling open-source microelectronics design flow with SkyWater 130nm Technology. -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
...In addition, professionals who want to use resampling, bootstrapping, or Monte Carlo simulations will find Statistics101 helpful. More information at https://statistics101.sourceforge.io/ -
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GeoDMA
Geographic feature extraction and data mining
GeoDMA is a plugin for TerraView software, used for geographical data mining. With a single image, the user can perform segmentation, attributes extraction, normalization and classification. -
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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JesseAi
Advanced AI-Powered Python Crypto Trading Bot 2026 - Free Backtesting
Jesse Bot: Advanced AI-Powered Python Best Crypto Trading Bot & Framework (2026) Jesse Bot — free open-source Python crypto trading bot & robust framework for cryptocurrency markets. Build, backtest, AI-optimize, and execute precise automated strategies with zero look-ahead bias. Use JesseGPT — built-in AI assistant — to write, debug, and refine strategies effortlessly, even as a beginner. Secure live trading on Binance, Bybit & major exchanges, full risk management, leverage/futures... -
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...The code includes built-in fitting procedures with a wide variety of constraints; stochastic SR energy loss; the tracking of synchrotron radiation (SR) Poynting vector; space charge models; various Monte Carlo procedures, etc. Contact: francoisgmeot@gmail.com Documentation (History of accelerators that zgoubi deals with, theory, tutorials): https://link.springer.com/book/10.1007/978-3-031-59979-8 https://link.springer.com/book/10.1007/978-3-031-16715-7, Chap. 14.
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CAMPARI
Software for molecular simulations and trajectory analysis
...CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. It focuses on a wide availability of algorithms for (advanced) sampling and is capable of combining Monte Carlo and molecular dynamics in seamless fashion. CAMPARI offers the user a very high level of control over all implemented features. For more information and features, please refer to the project's homepage at http://campari.sourceforge.net/V5 -
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PDP-OmniSim
PDP-OmniSim simulating parallel and distributed processing systems
PDP-OmniSim 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for large-scale simulations of networked systems and their emergent behaviors. 🎯 Key Scientific Contributions 🔬 Interdisciplinary Research Domains Computational... -
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MonteCarlo.jl
Classical and quantum Monte Carlo simulations in Julia
MonteCarlo.jl is a package implementing classical and quantum Monte Carlo simulations primarily for solid state physics. Currently the focus is on finding a overall design for the package and verifying that determinant Quantum Monte Carlo (DQMC) is working correctly. As such the package may still go through significant changes and the documentation may be outdated and incomplete. Note that classical Monte Carlo is also not a focus at this point. ...