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ORCIDMiguel A. Bessa
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- affiliation: Brown University, Providence, RI, USA
- affiliation (former): Delft University of Technology, The Netherlands
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2020 – today
- 2024
[j4]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa
:
Neural network relief: a pruning algorithm based on neural activity. Mach. Learn. 113(5): 2597-2618 (2024)- [i12]Gawel I. Kus, Miguel A. Bessa:
Gradient-free neural topology optimization. CoRR abs/2403.04937 (2024) - [i11]Chanwook Park, Sourav Saha, Jiachen Guo, Xiaoyu Xie, Satyajit Mojumder, Miguel A. Bessa, Dong Qian, Wei Chen, Gregory J. Wagner, Jian Cao, Wing Kam Liu:
Engineering software 2.0 by interpolating neural networks: unifying training, solving, and calibration. CoRR abs/2404.10296 (2024) - [i10]Suryanarayanan Manoj Sanu, Alejandro M. Aragon, Miguel A. Bessa:
Neural topology optimization: the good, the bad, and the ugly. CoRR abs/2407.13954 (2024) - [i9]Jiaxiang Yi, Ji Cheng, Miguel A. Bessa:
Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models. CoRR abs/2407.15110 (2024) - [i8]Harikrishnan Vijayakumaran, Jonathan B. Russ, Glaucio H. Paulino, Miguel A. Bessa:
Consistent machine learning for topology optimization with microstructure-dependent neural network material models. CoRR abs/2408.13843 (2024) - 2023
- [j3]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Continual prune-and-select: class-incremental learning with specialized subnetworks. Appl. Intell. 53(14): 17849-17864 (2023) - [j2]Bernardo P. Ferreira, F. M. Andrade Pires, Miguel A. Bessa:
CRATE: A Python package to perform fast material simulations. J. Open Source Softw. 8(88): 5594 (2023) - [i7]Aleksandr Dekhovich, Marcel H. F. Sluiter, David M. J. Tax, Miguel A. Bessa:
iPINNs: Incremental learning for Physics-informed neural networks. CoRR abs/2304.04854 (2023) - [i6]Aleksandr Dekhovich, Miguel A. Bessa:
Continual learning for surface defect segmentation by subnetwork creation and selection. CoRR abs/2312.05100 (2023) - 2022
- [i5]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Continual Prune-and-Select: Class-incremental learning with specialized subnetworks. CoRR abs/2208.04952 (2022) - [i4]Aleksandr Dekhovich, O. Taylan Turan, Jiaxiang Yi, Miguel A. Bessa:
Cooperative data-driven modeling. CoRR abs/2211.12971 (2022) - 2021
- [j1]Gawel I. Kus, Sybrand van der Zwaag, Miguel A. Bessa:
Sparse quantum Gaussian processes to counter the curse of dimensionality. Quantum Mach. Intell. 3(1): 1-12 (2021) - [c1]João Pedro Klock, Jhonatan Corrêa, Miguel A. Bessa, Janier Arias-Garcia, Felipe Barboza, Carmo Meinertz:
A New Automated Energy Meter Fraud Detection System Based on Artificial Intelligence. SBESC 2021: 1-8 - [i3]Dongil Shin, Andrea Cupertino, Matthijs H. J. de Jong, Peter G. Steeneken, Miguel A. Bessa, Richard A. Norte:
Spiderweb nanomechanical resonators via Bayesian optimization: inspired by nature and guided by machine learning. CoRR abs/2108.04809 (2021) - [i2]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Neural network relief: a pruning algorithm based on neural activity. CoRR abs/2109.10795 (2021) - [i1]Bernardo P. Ferreira, F. M. Andrade Pires, Miguel A. Bessa:
Adaptive Clustering-based Reduced-Order Modeling Framework: Fast and accurate modeling of localized history-dependent phenomena. CoRR abs/2109.11897 (2021)
Coauthor Index
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