Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation (AMISC) technique.
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Updated
May 14, 2024 - Python
Efficient framework for building surrogates of multidisciplinary systems using the adaptive multi-index stochastic collocation (AMISC) technique.
This repo is for copula based analysis on bivariate as well as multivariate data sets in ecology and related fields. For details and citation we refer to this publication: Ghosh et al., Advances in Ecological Research, vol 62,pp 409, 2020
🗿 Slides of talk "Python JSON Emoji crash story" at Django Meetup Berlin 2020-02-18; latest PDF: https://github.com/hartwork/slides_python_json_emoji_crash_story/releases/download/v4/python-json-emoji-crash-story-2020-02-18-v4.pdf
R code used for the analyses of the paper: Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using different taxa
Open-source constructor of surrogates and metamodels
😌 Encode and decode pairs of surrogate characters in Python 3
A Python utility for publishing a social media story built from archived web pages to multiple services.
Unicode Security Toolkit
A Julia package for generating timeseries surrogates
Automatic optimization and parallelization for Scientific Machine Learning (SciML)
Surrogate modeling and optimization for scientific machine learning (SciML)
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