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Miguel A Bessa

Showing results (1-10 of 8) with videos related to

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Advanced Materials (Deerfield Beach, Fla.)|October 15, 2019
Bayesian Machine Learning in Metamaterial Design: Fragile Becomes SupercompressibleMiguel A Bessa, Piotr Glowacki, Michael Houlder
Nanoscale Advances|May 23, 2022
Quantifying nanoscale forces using machine learning in dynamic atomic force microscopyAbhilash Chandrashekar, Pierpaolo Belardinelli, Miguel A Bessa, et al.
Computational Mechanics|May 22, 2023
Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimizationWing Kam Liu, Miguel A Bessa, Francisco Chinesta, et al.
Nature Communications|May 18, 2024
Centimeter-scale nanomechanical resonators with low dissipationAndrea Cupertino, Dongil Shin, Leo Guo, et al.
Advanced Materials (Deerfield Beach, Fla.)|October 25, 2021
Spiderweb Nanomechanical Resonators via Bayesian Optimization: Inspired by Nature and Guided by Machine LearningDongil Shin, Andrea Cupertino, Matthijs H J de Jong, et al.
Advanced Materials (Deerfield Beach, Fla.)|October 12, 2023
High-Strength Amorphous Silicon Carbide for NanomechanicsMinxing Xu, Dongil Shin, Paolo M Sberna, et al.
Nature Communications|March 25, 2025
Pentagonal photonic crystal mirrors: scalable lightsails with enhanced acceleration via neural topology optimizationLucas Norder, Shunyu Yin, Matthijs H J de Jong, et al.
Nature Communications|October 1, 2025
Unifying machine learning and interpolation theory via interpolating neural networksChanwook Park, Sourav Saha, Jiachen Guo, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Advanced Materials (Deerfield Beach, Fla.)|October 15, 2019
Bayesian Machine Learning in Metamaterial Design: Fragile Becomes SupercompressibleMiguel A Bessa, Piotr Glowacki, Michael Houlder
Nanoscale Advances|May 23, 2022
Quantifying nanoscale forces using machine learning in dynamic atomic force microscopyAbhilash Chandrashekar, Pierpaolo Belardinelli, Miguel A Bessa, et al.
Computational Mechanics|May 22, 2023
Special issue of computational mechanics on machine learning theories, modeling, and applications to computational materials science, additive manufacturing, mechanics of materials, design and optimizationWing Kam Liu, Miguel A Bessa, Francisco Chinesta, et al.
Nature Communications|May 18, 2024
Centimeter-scale nanomechanical resonators with low dissipationAndrea Cupertino, Dongil Shin, Leo Guo, et al.
Advanced Materials (Deerfield Beach, Fla.)|October 25, 2021
Spiderweb Nanomechanical Resonators via Bayesian Optimization: Inspired by Nature and Guided by Machine LearningDongil Shin, Andrea Cupertino, Matthijs H J de Jong, et al.
Advanced Materials (Deerfield Beach, Fla.)|October 12, 2023
High-Strength Amorphous Silicon Carbide for NanomechanicsMinxing Xu, Dongil Shin, Paolo M Sberna, et al.
Nature Communications|March 25, 2025
Pentagonal photonic crystal mirrors: scalable lightsails with enhanced acceleration via neural topology optimizationLucas Norder, Shunyu Yin, Matthijs H J de Jong, et al.
Nature Communications|October 1, 2025
Unifying machine learning and interpolation theory via interpolating neural networksChanwook Park, Sourav Saha, Jiachen Guo, et al.
Pageof 1