Active Subspace Methods for Data-Intensive Inverse Problems
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.
- Research Organization:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- SC0011089
- OSTI ID:
- 1353429
- Report Number(s):
- DE-SC0011089
- Country of Publication:
- United States
- Language:
- English
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