Search Results for "parameter estimation"
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Showing 38 open source projects for "parameter estimation"
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Catalyst.jl
Chemical reaction network and systems biology interface
...Leveraging ModelingToolkit and Symbolics.jl, Catalyst enables large-scale simulations through auto-vectorization and parallelism. Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy simulation and parameter estimation of mass action ODE models, Chemical Langevin SDE models, stochastic chemical kinetics jump process models, and more. Generated models can be used with solvers throughout the broader SciML ecosystem, including higher-level SciML packages (e.g. for sensitivity analysis, parameter estimation, machine learning applications, etc). -
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Sygil WebUI
Stable Diffusion web UI
Sygil WebUI is a browser-based interface for running Stable Diffusion image generation locally or on a server, wrapping common text-to-image and image-to-image workflows into a practical UI. It provides multiple UI modes (including a legacy Gradio interface) and focuses on making iterative prompting, parameter tuning, and post-processing accessible without writing code. The UI exposes core generation controls like resolution, CFG guidance, sampling steps, samplers, seeds, and batch... -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. -
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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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Qwen-Image
Qwen-Image is a powerful image generation foundation model
Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence. -
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SMIT
SMIT is a 3-phase Induction Motor Simulator, with or without failures
SMIT, Simulador do Motor de Indução Trifásico, or 3-phase Induction Motor Simulator, is an open source program developed in Python that allows you to simulate an induction motor using catalog data or data obtained through tests. This application was developed by master Lucas Henrique Gonçalves Ribeiro and his advisor, professor Dr. Lane Maria Rabelo, from the Postgraduate Program in Electrical Engineering (PPGEL) at the Federal University of São João del-Rei. The idea of the work was to... -
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
...It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as plotting and exporting to various file formats - Report generation - Code generation, co-simulation and model exchange The following class of problems can be solved by DAE Tools: - Initial value problems of implicit form - Index-1 DAE systems - With lumped or distributed parameters - Steady-state or dynamic - Continuous with some elements of event-driven systems -
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pattern_classification
A collection of tutorials and examples for solving machine learning
The pattern_classification repository is an educational project that provides tutorials, examples, and reference materials related to machine learning and statistical pattern recognition. The project aims to help learners understand the process of building predictive models by presenting structured explanations and practical examples. It includes notebooks and guides that demonstrate data preprocessing, feature extraction, model training, and evaluation techniques used in machine learning... -
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SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem. -
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SPINspiral
A gravitational-wave parameter-estimation code for LIGO/Virgo
SPINspiral is a parameter-estimation code for the analysis of gravitational-wave signals detected by LIGO/Virgo. -
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analyseMCMC
Analyse output from MCMC codes like SPINspiral and lalinference_mcmc
analyseMCMC post-processes, analyses and plots output from the LIGO/Virgo gravitational-wave inspiral parameter-estimation codes SPINspiral and lalinference_mcmc. -
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jags-zibg
Zero-inflated bivariate geometric distributions in JAGS
The JAGS ZIBGeometric module extends JAGS by providing a zero-inflated bivariate geometric distribution class. Currently, it only supports probability mass computations in posterior parameter distribution estimation. -
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types in... -
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ConvNet Burden
Memory consumption and FLOP count estimates for convnets
...It lets users compute approximate burdens (in FLOPs, memory) for standard image classification CNN models (e.g. ResNet, VGG) based on network definitions. The tool helps researchers compare the computational efficiency of architectures or quantify resource needs. Estimation of memory consumption (e.g. feature map sizes, parameter storage). Support for multiple network definitions/architectures. Estimation of memory consumption (e.g. feature map sizes, parameter storage). Estimation of FLOPs (floating point operations) for CNN architectures. -
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ATLAS_mPBPK
Modeling and Simulation of mPBPK models
ATLAS mPBPK is a MATLAb-based tool for modeling and Simulation of minimal Physiology Based Pharmacokinetic (mPBPK) models of small and large molecules. The tool enables the users to perform: i) PK data visualization, ii) simulation, iii) parameter optimization, and iv) local sensitivity analysis (SA) of mPBPK models in a simple and efficient manner. -
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The Crux
Experimental data modelling and simulation
Parameter optimization program with objective functions for the quantitative estimation of biochemical/biophysical reaction parameters (equilibrium and rate constants, etc.) -
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...Algorithm implementation for population pharmacokinetic analysis: The current project describes the marriage between PBPK modeling and population-based statistical analysis. The latter is necessary for parameter estimation when individual-level data is available. A critical aspect of this coupling is the implementation of an algorithm that would allow the performance of population-based statistical analysis. Although novelty is encouraged in regards to the algorithm, proposals could entertain approaches such as: a. Implementing the non-linear mixed effects theory, b. ...
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Weibull 2 e 3p Maximum Likelihood parameter estimation, for complete data, left truncated data, righttruncated data, left and right truncated data.
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SoloDel
Somatic Low-frequent Deletion Caller Model
...SoloDel is specialized for identifying somatic deletions with frequently existing sampling issues : low mutational frequency in cell population and absence of the matched control samples. The important features of SoloDel are: • Estimation of mutational frequency in a mixed disease sample without matched control • Improved somatic deletion calling based on the probabilistic model with the parameter estimation -
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...The following features were implemented in OpenFLUX2, which were not present in original software: integrated support for calculation and analysis of parallel labeling experiments (PLE), extended statistical analysis of parameter estimation results, calculation of fluxes and measurements correlation, structural identifiability analysis and elements of experimental design.
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LoDel
A probabilistic model for detecting low-frequent somatic deletion
...LoDel is specialized for identifying somatic deletions with frequently existing sampling issues : low mutational frequency in cell population and absence of the matched control samples. The important features of LoDel are: •Estimation of accurate mutation frequency in a mixed disease sample •Improved somatic deletion calling based on the probabilistic model with the parameter estimation -
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
Find here the model, code, and example results of parameter fitting/calibration and sensitivity analysis for an agent-based model using NetLogo and R. The corresponding manuscript is published in Journal of Artificial Societies and Social Simulation as: Thiele JC, Kurth W, Grimm V (2014): Facilitating parameter estimation and sensitivity analysis of agent-based models: a cookbook using NetLogo and R. -
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CADET
Chromatography Analysis and Design Toolkit
...The CADET solver covers a wide range of GRM variants, combining different transport and binding models with state-of-the-art mathematical algorithms and scientific computing techniques. The CADET framework also comprises a MATLAB interface and standard routines for parameter estimation, process optimization and experimental design. CADET is freely distributed as a contribution to the scientific community. If you find it useful for your own work, we would appreciate acknowledgements of the CADET software and citations of our papers: http://doi.org/10.1016/j.compchemeng.2010.03.008 http://doi.org/10.1016/j.compchemeng.2018.02.025 -
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Weibull-based reliability toolkit for R
R package for Weibull analysis on (life-)time observations.
This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/. -
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modelMaGe2.0 is a software application that automatically generates mathematical models in Copasi format (www.Copasi.org) by removing model components from a given master model. Candidate models can automatically be fitted to provided data.
