Data-Drive Site Characterization for Benchmark Examples: Sparse Bayesian Learning versus Gaussian Process Regression
Author:
Affiliation:
1. Professor, Dept. of Civil Engineering, National Taiwan Univ., #1 Roosevelt Rd. Sect. 4, Taipei 10617, Taiwan (corresponding author). ORCID: .
2. Professor, Dept. of Urban and Civil Engineering, Tokyo City Univ., Tokyo 158-8557, Japan. ORCID:
Publisher
American Society of Civil Engineers (ASCE)
Subject
Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering
Link
https://ascelibrary.org/doi/pdf/10.1061/AJRUA6.RUENG-983
Reference22 articles.
1. Transitional Markov Chain Monte Carlo: Observations and Improvements
2. Bishop, C. M., and N. M. Nasrabadi. 2006. Pattern recognition and machine learning. New York: Springer.
3. Transitional Markov Chain Monte Carlo Method for Bayesian Model Updating, Model Class Selection, and Model Averaging
4. 3D Probabilistic Site Characterization by Sparse Bayesian Learning
5. Characterizing Uncertain Site-Specific Trend Function by Sparse Bayesian Learning
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