Ecosyste.ms sponsors
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An open API service aggregating public data about GitHub Sponsors.
A nonprofit dedicated to the advancement of predictive science through research partnerships and education.
Funding Links: https://github.com/sponsors/uqfoundation, http://uqfoundation.org/pages/donate.html
Uncertainty Quantification Foundation is an organization whose mission is: (1) to broaden the study and application of uncertainty quantification, and (2) to support the development and dissemination of advanced tools, technologies, and methodologies for UQ. We are scientists, engineers, mathematicians, data scientists, and statisticians working to push forward the field of uncertainty quantification, provide a bridge between the work of researchers and organizations that can drive innovation across the public and private sectors, and advance fundamental science that can be used to develop advanced tools and technologies to foster innovation for the broader public benefit.
A central focus of Uncertainty Quantification Foundation is fundamental scientific research in the fields of uncertainty quantification and predictive science. We employ scientists and researchers from various fields, with specialties in the mathematics, statistics, data science, and engineering, to pursue the expansion of knowledge within uncertainty quantification. These researchers work to develop new mathematical theories underpinning UQ, discover new computational methods to approach experiments under uncertainty, and increase knowledge of fundamental principles that will explore how uncertainty quantification broadly interacts with the natural sciences and engineering.
Our objective is to have all research published in the form of peer-reviewed articles or chapters in scientific journals, books, or trade publications. Any computational frameworks developed either through our research or as the primary focus of our research will be made freely available to the public under an open source software license, and will have no associated fee to download current releases or development version source code.
Research at Uncertainty Quantification Foundation is funded through our general fund, donations from individual persons, public and private grants, fees generated from our Education and Advisory programs, and through sponsored research.
serialize all of Python
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