Mikel Landajuela
Orcid: 0000-0002-4804-6513Affiliations:
- Lawrence Livermore National Laboratory, San Francisco Bay Area, CA, USA
According to our database1,
Mikel Landajuela
authored at least 14 papers
between 2015 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on orcid.org
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on github.com
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Bibliography
2025
SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation.
IEEE Trans. Evol. Comput., August, 2025
CoRR, May, 2025
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2023
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition.
CoRR, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Intracardiac Electrical Imaging Using the 12-Lead ECG: A Machine Learning Approach Using Synthetic Data.
Proceedings of the Computing in Cardiology, 2022
2021
CoRR, 2021
Improving exploration in policy gradient search: Application to symbolic optimization.
CoRR, 2021
Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients.
Proceedings of the 9th International Conference on Learning Representations, 2021
2015
Fully decoupled time-marching schemes for incompressible fluid/thin-walled structure interaction.
J. Comput. Phys., 2015