Bernstein--von Mises Theorems and Uncertainty Quantification for Linear Inverse Problems

Mathematics

• Uncertainty Quantification 86%
• Linear Inverse Problems 84%
• Elliptic Boundary Value Problems 69%
• Inverse Problem 52%
• Efficient Estimator 39%
• Gaussian White Noise 38%
• Gaussian Measure 38%
• Reproducing Kernel Hilbert Space 36%
• Linear Functional 32%
• Posterior distribution 32%
• Bayesian Approach 32%
• Penalty 30%
• Heat Equation 30%
• Elliptic Problems 29%
• Probability Measure 28%
• Theorem 26%
• Ball 26%
• Valid 24%
• Cover 23%
• Unknown 21%
• Norm 19%
• Standards 18%

Business & Economics

• Inverse Problem 100%
• Quantification 68%
• Hilbert Space 51%
• Posterior Distribution 42%
• Kernel 39%
• Uncertainty 38%
• Bayesian Approach 36%
• Penalty 29%
• Guarantee 26%
• Estimator 25%

Engineering & Materials Science

• Boundary value problems 72%
• Inverse problems 70%
• Hilbert spaces 43%
• Uncertainty 40%
• Hot Temperature 15%