Search Results for "monte carlo"
Sort By:
Showing 204 open source projects for "monte carlo"
View related business solutions-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
1
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. -
2
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. -
3
EMC: Enhanced Monte Carlo; A multi-purpose modular and easy extendable solution to molecular and mesoscale simulations
-
4
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. -
Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
-
5
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. ... -
6
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
-
7
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. -
8
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. ... -
9
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. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
10
Kimi k1.5
Scaling Reinforcement Learning with LLMs
...By using techniques like partial rollouts to improve training efficiency and applying sophisticated policy optimization methods, the developers demonstrate that strong ability can emerge without relying on complex solutions like Monte Carlo tree search or value functions. Kimi-k1.5 is trained jointly on text and vision data, giving it true multimodal reasoning capabilities where it can interpret and generate content across modalities in a unified way. -
11
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... -
12
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. -
13
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. -
14
RMCProfile
Big box modeling for total scattering via the Reverse Monte Carlo
-
15
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 -
16
JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.
-
17
MCPower
MCPower — simple Monte Carlo power analysis for complex models
MCPower-GUI is a desktop application that provides a graphical interface for the MCPower Monte Carlo power analysis library. It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). ... -
18
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. -
19
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. -
20
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. -
21
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/ -
22
Basic Blind Chess
Blind Chess using Taiwan rules
...This application is using Taiwan rule. AI is using basic minimax tree structure and some rules. Advanced algorithm such as Upper Confidence bounds applied to Trees and Monte Carlo Tree Search are NOT used. This app is single player vs computer only. For English user, Christakis Giorgios made Software Requirements Specification(pdf file), it will help anyone that downloads this application to understand basic blind chess and use it. You can download this pdf in Files->Specification folder. -
23
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. -
24
...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.
-
25
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
