EB-RANSAC: Random Sample Consensus based on Energy-Based Model
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911511721541632 |
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| author | Yasuda, Muneki Watanabe, Nao Sekimoto, Kaiji |
| author_facet | Yasuda, Muneki Watanabe, Nao Sekimoto, Kaiji |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_12525 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | EB-RANSAC: Random Sample Consensus based on Energy-Based Model Yasuda, Muneki Watanabe, Nao Sekimoto, Kaiji Machine Learning Disordered Systems and Neural Networks 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. |
| title | EB-RANSAC: Random Sample Consensus based on Energy-Based Model |
| topic | Machine Learning Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2603.12525 |