Rigid transformations for stabilized lower dimensional space to support subsurface uncertainty quantification and interpretation
From MaRDI portal
Publication:6578296
DOI10.1007/s10596-024-10278-xzbMath1541.86023MaRDI QIDQ6578296
Michael J. Pyrcz, Ademide O. Mabadeje
Publication date: 25 July 2024
Published in: Computational Geosciences (Search for Journal in Brave)
reservoir characterizationmachine learningdimensionality reductionuncertainty quantificationrigid transformationsanalog selection
Geostatistics (86A32) Potentials, prospecting (86A20) Statistical aspects of big data and data science (62R07)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Learning a factor model via regularized PCA
- Comparing training-image based algorithms using an analysis of distance
- Non-parametric detection of meaningless distances in high dimensional data
- Kernel principal component analysis for efficient, differentiable parametrization of multipoint geostatistics
- Semisupervised learning from dissimilarity data
- Upper bounds for Kruskal's stress
- Instability results for Euclidean distance, nearest neighbor search on high dimensional Gaussian data
- A manifold learning approach to dimensionality reduction for modeling data
- Efficient real-time reservoir management using adjoint-based optimal control and model updating
- Diffusion maps
- Modern multidimensional scaling. Theory and applications.
- Discussion of a set of points in terms of their mutual distances.
- Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
- Multidimensional scaling. I: Theory and method
- Dynamic mode decomposition of numerical and experimental data
- Spectral analysis of nonlinear flows
- The quickhull algorithm for convex hulls
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
This page was built for publication: Rigid transformations for stabilized lower dimensional space to support subsurface uncertainty quantification and interpretation