Search Results for "process"
Sort By:
Showing 15 open source projects for "process"
View related business solutions-
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
STK
a Small (Matlab/Octave) 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), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.). -
2
DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options. -
3
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. -
4
GPMfit
Gaussian Process Model Fitting
Gaussian Process model for fitting deterministic simulator output. Establish efficient and reliable likelihood optimization through hybridized DIRECT-BFGS and multi-start BFGS algorithms. Programming Language: Matlab. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
Excelsi-R
Excel's Interface to R
Excelsi-R is an Excel add-in that allows Excel spreadsheets to harness the power of the R statistical language by connecting to a running R process. R does not need to be installed on the computer running Excel, but it does require access to an R instance running Rserve (which can be on a remote computer). It supports incorporating R plots and graphs in an Excel workbook. -
6
Hrothgar Parallel LM/MCMC Minimizer
A versatile MCMC and downhill optimization engine
Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator by Andisheh Mahdavi of San Francisco State University. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays). It is probably adaptable enough to be applied to your merit function if you can write it in C. -
7
PhEq_bootstrap
FDA's f2 computation with bootstrap technique
This program was developed as a help in establishing pharmaceutical equivalence by use of FDA f2 coefficient. It was designed to help with f2 computation in cases when intra- and inter-batch variability is large, namely RSD>10%. The use of statistical bootstrap technique allows to implement confidence interval (CI) into the f2 coefficients resulting in overcoming of their major drawback in the original metrics. The algorithm provides possible “worst case scenario” of f2 values, thus... -
8
QPNet
Synchronous Petri Nets' emulator
QPNet (Quick Petri Net) is a fast Petri Nets' emulator, created by students of Moscow State Technical University of Radio Engineering, Electronics and Automation. It brings benefits for the educational process, while being under further development and extension. QPNet это быстрый эмулятор сетей Петри, созданный студентами МИРЭА. Он применяется в учебном процессе, а так же продолжает разрабатываться и эволюционировать. -
9
phcfM
R package for modelling anthropogenic deforestation
...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
10
The project simulates a generic agent based market model. The aim is to explore intimately, by simulation, the process of price formation and the market microstructure.
-
11
T3S Tool
Learning Stochastic Discrete Event Systems
Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes. -
12
Optimization tool that mimics the darwinian reproduction, selection, mutation process. It has 2 components: the optimization algorithm and an interpretar to define function to optimize and constraints. It is all written in java (netbeans).
-
13
MultiBase Calc framework
A multi-base calc framework
This framework allows you to create your own Operators, Math Const and base, to process on any mathematical expression. -
14
The CRISP package here developed utilizes an algorithm that describes a many-body intranuclear cascade (INC) and evaporation/fission/multifragmentation competition process.
-
15
R package kOO
implementing k-spatial entropy methodology
The R package to be built aims at implementing what I did in a few scripts for the preparation of the papers I published in CaGEO and TGIS (see below). Basically this is related to the computation of the distribution of k co-occurrences of spatial events (generalising the contiguity distributions - 2 co-occurrences at distance 0) to derive spatial clustering statistics (mainly using the Shannon entropy, then called the k-spatial entropy) and methods linked to this: SOOk, SelSOOk (see caGEO...
- Previous
- You're on page 1
- Next
