Skip to main navigation
Skip to search
Skip to main content
TU Delft Research Portal Home
Help & FAQ
Home
Research units
Researchers
Research output
Datasets
Projects
Press/Media
Prizes
Activities
Search by expertise, name or affiliation
Consistency of Bayesian inference with Gaussian process priors for a parabolic inverse problem
Hanne Kekkonen
*
*
Corresponding author for this work
Statistics
Research output
:
Contribution to journal
›
Article
›
Scientific
›
peer-review
4
Citations (Scopus)
92
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Consistency of Bayesian inference with Gaussian process priors for a parabolic inverse problem'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Bayesian Inference
100%
Gaussian Process
100%
Parabolic
100%
Bounded Domain
50%
True Parameter
50%
Number
50%
Fixed Time
50%
Evaluation Point
50%
Gaussian Distribution
50%
Optimality
50%
Minimax
50%
Posterior Distribution
50%
Heat Equation
50%
Nonparametric Procedure
50%
Linear Inverse Problems
50%
Bayesian
50%
Nonlinear
50%
Bounds
50%
Smooth Function
50%
Posterior Mean
50%
Data Consist
50%
INIS
gaussian processes
100%
data
100%
convergence
66%
heat
33%
distribution
33%
values
33%
evaluation
33%
absorption
33%
nonlinear problems
33%
equations
33%
errors
33%
performance
33%
solutions
33%
contraction
33%