[HTML][HTML] Explainable ai: A review of machine learning interpretability methods
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …
with machine learning systems demonstrating superhuman performance in a significant …
[HTML][HTML] On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness
In recent times, composite indicators have gained astounding popularity in a wide variety of
research areas. Their adoption by global institutions has further captured the attention of the …
research areas. Their adoption by global institutions has further captured the attention of the …
Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses
Sensitivity analysis is now considered a standard practice in environmental modeling.
Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been …
Several open-source libraries, such as the Sensitivity Analysis Library (SALib), have been …
[HTML][HTML] The future of sensitivity analysis: an essential discipline for systems modeling and policy support
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
[图书][B] Surrogates: Gaussian process modeling, design, and optimization for the applied sciences
RB Gramacy - 2020 - taylorfrancis.com
Computer simulation experiments are essential to modern scientific discovery, whether that
be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are …
be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are …
[PDF][PDF] SALib: An open-source Python library for sensitivity analysis
SALib contains Python implementations of commonly used global sensitivity analysis
methods, including Sobol (Sobol'2001, Andrea Saltelli (2002), Andrea Saltelli et al.(2010)) …
methods, including Sobol (Sobol'2001, Andrea Saltelli (2002), Andrea Saltelli et al.(2010)) …
[HTML][HTML] A framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs
Abstract Cardiac digital twins (Cardiac Digital Twin (CDT) s) of human electrophysiology
(Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that …
(Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that …
Sensitivity analysis: A review of recent advances
E Borgonovo, E Plischke - European Journal of Operational Research, 2016 - Elsevier
The solution of several operations research problems requires the creation of a quantitative
model. Sensitivity analysis is a crucial step in the model building and result communication …
model. Sensitivity analysis is a crucial step in the model building and result communication …
A review on global sensitivity analysis methods
B Iooss, P Lemaître - … management in simulation-optimization of complex …, 2015 - Springer
This chapter makes a review, in a complete methodological framework, of various global
sensitivity analysis methods of model output. Numerous statistical and probabilistic tools …
sensitivity analysis methods of model output. Numerous statistical and probabilistic tools …
[图书][B] Uncertainty quantification: theory, implementation, and applications
RC Smith - 2013 - SIAM
The norm on a vector space generalizes the concept of the length for a vector. Similarly, we
will typically impose inner products which provide measures of orthogonality as an …
will typically impose inner products which provide measures of orthogonality as an …