Zobrazeno 1 - 10
of 5 152
pro vyhledávání: '"A. Muga"'
Solving PDEs with machine learning techniques has become a popular alternative to conventional methods. In this context, Neural networks (NNs) are among the most commonly used machine learning tools, and in those models, the choice of an appropriate
Externí odkaz:
http://arxiv.org/abs/2305.09578
The efficient approximation of parametric PDEs is of tremendous importance in science and engineering. In this paper, we show how one can train Galerkin discretizations to efficiently learn quantities of interest of solutions to a parametric PDE. The
Externí odkaz:
http://arxiv.org/abs/2304.01722
The Adaptive Stabilized Finite Element method (AS-FEM) developed in Calo et. al. combines the idea of the residual minimization method with the inf-sup stability offered by the discontinuous Galerkin (dG) frameworks. As a result, the discretizations
Externí odkaz:
http://arxiv.org/abs/2303.17982
Heat rectifiers would facilitate energy management operations such as cooling, or energy harvesting, but devices of practical interest are still missing. Understanding heat rectification at a fundamental level is key to help us find or design such de
Externí odkaz:
http://arxiv.org/abs/2302.13874
Autor:
Khatia Munguambe, Quique Bassat, Mahbubur Rahman, Sibone Mocumbi, Cynthia G Whitney, Amy Wise, Shams El Arifeen, Meerjady Sabrina Flora, Soter Ameh, Emily S Gurley, Mustafizur Rahman, Ariel Nhacolo, Cheick Bougadari Traore, Inacio Mandomando, Clara Menendez, Janet Agaya, Jane Juma, Shabir A Madhi, Tadesse Gure, George Aol, Hennie Lombaard, Ziyaad Dangor, James Bunn, Samba O Sow, Amara Jambai, Dickson Gethi, Sanwarul Bari, Natalia Rakislova, Tacilta Nhampossa, Maria Maixenchs, Mohammed Kamal, Joseph Oundo, Lola Madrid, Tahmina Shirin, Ikechukwu Udo Ogbuanu, Addisu Alemu, Hailemariam Legesse, Awa Traore, Portia C Mutevedzi, Helina Heluf, Victor Akelo, Dickens Onyango, Richard Omore, Yasmin Adam, Peter Otieno, Margaret Mannah, Karen L Kotloff, Milagritos D Tapia, Rima Koka, Mohammad Zahid Hossain, Dickens Kowuor, Tom Sesay, James Squire, Francis Moses, Kitiezo Aggrey Igunza, Andrew Moseray, Afruna Rahman, Nana Kourouma, Seydou Sissoko, Rosauro Varo, Sana Mahtab, Martin Hale, Jeanie du Toit, Zachary J Madewell, Dianna M Blau, Fatima Solomon, Gillian Sorour, Jeannette Wadula, Karen Petersen, Sanjay G Lala, Sithembiso Velaphi, Richard Chawana, Nellie Myburgh, Shahana Parveen, Mahbubul Hoque, Saria Tasnim, Ferdousi Islam, Farida Ariuman, Mohammad Mosiur Rahman, Dilruba Ahmed, Fikremelekot Temesgen, Melisachew Mulatu Yeshi, Mahlet Abayneh Gizaw, Stian MS Orlien, Solomon Ali, Peter Nyamthimba Onyango, Richard Oliech, Joyce Akinyi Were, Thomas Misore, Harun Owuor, Christopher Muga, Christine Ochola, Ashka Mehta, Brigitte Gaume, Adama Mamby Keita, Diakaridia Kone, Diakaridia Sidibe, Doh Sanogo, Kounandji Diarra, Tiéman Diarra, Kiranpreet Chawla, Zara Manhique, Fatmata Bintu Tarawally, Martin Seppeh, Ronald Mash, Julius Ojulong, Babatunde Duduyemi, Alim Swaray-Deen, Okokon Ita, Cornell Chukwuegbo, Sulaiman Sannoh, Princewill Nwajiobi, Erick Kaluma, Oluseyi Balogun, Carrie Jo Cain, Solomon Samura, Samuel Pratt, Joseph Kamanda Sesay, Osman Kaykay, Binyam Halu, Francis Smart, Sartie Kenneh, Ferdousi Begum, Priya Mehta-Gupta Das, Ogony Benard Oluoch, Caleb K Sagam, Ronita Luke, Milton Kincardett, Elisio G Xerinda, Markus Roos Breines, Ketema Degefa, J. Anthony G Scott, Kazi Munisul Islam, Parminder S Suchdev, Nelesh P. Govender, Peter J. Swart, Nawshad Uddin Ahmed, Alexander M. Ibrahim, Sharon M. Tennant, Carol L. Greene, J. Kristie Johnson, Karen D. Fairchild, Uma U. Onwuchekwa, Joseph Bangura
Publikováno v:
BMJ Global Health, Vol 9, Iss 12 (2024)
Introduction Malnutrition contributes to 45% of all childhood deaths globally, but these modelled estimates lack direct measurements in countries with high malnutrition and under-5 mortality rates. We investigated malnutrition’s role in infant and
Externí odkaz:
https://doaj.org/article/080ae47446d94bdfba6536fa9e658e9e
Petrov-Galerkin formulations with optimal test functions allow for the stabilization of finite element simulations. In particular, given a discrete trial space, the optimal test space induces a numerical scheme delivering the best approximation in te
Externí odkaz:
http://arxiv.org/abs/2212.12695
A Deep Double Ritz Method (D$^2$RM) for solving Partial Differential Equations using Neural Networks
Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields a saddle-point (min-max) problem over the so-called trial and test spa
Externí odkaz:
http://arxiv.org/abs/2211.03627
When using Neural Networks as trial functions to numerically solve PDEs, a key choice to be made is the loss function to be minimised, which should ideally correspond to a norm of the error. In multiple problems, this error norm coincides with--or is
Externí odkaz:
http://arxiv.org/abs/2210.14129
We introduce an adaptive superconvergent finite element method for a class of mixed formulations to solve partial differential equations involving a diffusion term. It combines a superconvergent postprocessing technique for the primal variable with a
Externí odkaz:
http://arxiv.org/abs/2210.00390
Autor:
Delgado, F., Muga, J. G.
Publikováno v:
Physica E: Low-dimensional Systems and Nanostructures Volume 74, November 2015, Pages 108-114
We put forward a model that describes a decaying and evanescent point source of non-interacting quantum waves in 1D. This point-source assumption allows for a simple description that captures the essential aspects of the dynamics of a wave traveling
Externí odkaz:
http://arxiv.org/abs/2208.14169