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Combining graph deep learning and London dispersion interatomic potentials: A case study on pnictogen chalcohalides

Autor: Kılıç, Çetin, Güler-Kılıç, Sümeyra

Publikováno v: J. Chem. Phys. 161, 174106 (2024)

Machine-learning interatomic potential models based on graph neural network architectures have the potential to make atomistic materials modeling widely accessible due to their computational efficiency, scalability, and broad applicability. The train

Externí odkaz: http://arxiv.org/abs/2411.01197

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Enhancement of Approximation Spaces by the Use of Primals and Neighborhood

Autor: Güler, A. Çaksu

Rough set theory is one of the most widely used and significant approaches for handling incomplete information. It divides the universe in the beginning and uses equivalency relations to produce blocks. Numerous generalized rough set models have been

Externí odkaz: http://arxiv.org/abs/2411.04133

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Coverage measurement in model-based testing of web applications: Tool support and an industrial experience report

Autor: Garousi, Vahid, Keleş, Alper Buğra, Balaman, Yunus, Mermer, Alper, Güler, Zeynep Özdemir

There are many widely used tools for measuring test-coverage and code-coverage. Test coverage is the ratio of requirements or other non-code artifacts covered by a test suite, while code-coverage is the ratio of source code covered by tests. Almost a

Externí odkaz: http://arxiv.org/abs/2408.06148

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Refining Tuberculosis Detection in CXR Imaging: Addressing Bias in Deep Neural Networks via Interpretability

Autor: Güler, Özgür Acar, Günther, Manuel, Anjos, André

Automatic classification of active tuberculosis from chest X-ray images has the potential to save lives, especially in low- and mid-income countries where skilled human experts can be scarce. Given the lack of available labeled data to train such sys

Externí odkaz: http://arxiv.org/abs/2407.14064

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Characterizations of a Lorentzian Manifold with a semi-symmetric metric connection

Autor: De, Uday Chand, De, Krishnendu, Güler, Sinem

Publikováno v: Publ. Math. Debrecen (2024) 329-341

In this article, we characterize a Lorentzian manifold $\mathcal{M}$ with a semi-symmetric metric connection. At first, we consider a semi-symmetric metric connection whose curvature tensor vanishes and establish that if the associated vector field i

Externí odkaz: http://arxiv.org/abs/2406.16108

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MeshPose: Unifying DensePose and 3D Body Mesh reconstruction

Autor: Lê, Eric-Tuan, Kakolyris, Antonis, Koutras, Petros, Tam, Himmy, Skordos, Efstratios, Papandreou, George, Güler, Rıza Alp, Kokkinos, Iasonas

Publikováno v: CVPR 2024

DensePose provides a pixel-accurate association of images with 3D mesh coordinates, but does not provide a 3D mesh, while Human Mesh Reconstruction (HMR) systems have high 2D reprojection error, as measured by DensePose localization metrics. In this

Externí odkaz: http://arxiv.org/abs/2406.10180

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