EB-RANSAC: Random Sample Consensus based on Energy-Based Model
Yasuda, Muneki, Watanabe, Nao, Sekimoto, Kaiji
Random sample consensus (RANSAC), which is based on a repetitive sampling from a given dataset, is one of the most popular robust estimation methods. In this study, an energy-based model (EBM) for robust estimation that has a similar scheme to RANSAC, energy-based RANSAC (EB-RANSAC), is proposed. EB-RANSAC is applicable to a wide range of estimation problems similar to RANSAC. However, unlike RANSAC, EB-RANSAC does not require a troublesome sampling procedure and has only one hyperparameter. The effectiveness of EB-RANSAC is numerically demonstrated in two applications: a linear regression and maximum likelihood estimation.
Mar-16-2026
- Country:
- Asia > Japan (0.04)
- Europe > Switzerland
- Basel-City > Basel (0.04)
- North America > United States
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- Research Report > New Finding (0.34)
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- Education (0.46)