< Back to previous page
Researcher
Arun Kaintura
- Disciplines:Scientific computing, Computer theory, Computer hardware, Other computer engineering, information technology and mathematical engineering
Affiliations
- Department of Information technology (Department)
Member
From12 Feb 2015 → 22 Sep 2019
Publications
1 - 6 of 6
- Fast characterization of input-output behavior of non-charge-based logic devices by machine learning(2020)
Authors: Arun Kaintura, Kyle Powers Foss, Odysseas Zografos, Ivo Couckuyt, Adrien Vaysset, Tom Dhaene, Bart Soree
- Data-efficient machine learning for physics-based simulations(2019)
Authors: Arun Kaintura
Number of pages: 1 - Machine learning for fast characterization of magnetic logic devices(2018)
Authors: Arun Kaintura, Kyle Powers Foss, Ivo Couckuyt, Tom Dhaene, Odysseas Zografos, Adrien Vaysset, Bart Soree
Pages: 1 - 3 - Review of polynomial chaos-based methods for uncertainty quantification in modern integrated circuits(2018)
Authors: Arun Kaintura, Tom Dhaene, Domenico Spina
- Measurement uncertainty propagation in transistor model parameters via polynomial chaos expansion(2017)
Authors: Alessandra Petrocchi, Arun Kaintura, Gustavo Avolio, Domenico Spina, Tom Dhaene, Antonio Raffo, Dominique MM-P Schreurs
Pages: 572 - 574 - A Kriging and stochastic collocation ensemble for uncertainty quantification in engineering applications(2017)
Authors: Arun Kaintura, Domenico Spina, Ivo Couckuyt, Luc Knockaert, Wim Bogaerts, Tom Dhaene
Pages: 935 - 949