Zobrazeno 1 - 10
of 112 062
pro vyhledávání: '"Arslan AT"'
Autor:
Lu, Tao, Dhiman, Ankit, Srinath, R, Arslan, Emre, Xing, Angela, Xiangli, Yuanbo, Babu, R Venkatesh, Sridhar, Srinath
Novel-view synthesis is an important problem in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent methods like 3D Gaussian Splatting (3DGS) have become the preferred method for this task, providing high-quali
Externí odkaz:
http://arxiv.org/abs/2412.13547
Autor:
Lee, Yohan, Herbig, Jonas, Arslan, Serkan, Ludescher, Dominik, Ubl, Monika, Georg, Andreas, Hentschel, Mario, Giessen, Harald
Colour printing based on metallic or dielectric nanostructures has revolutionized colour science due to its unprecedented subwavelength resolution. Evidently, the evolution towards the active control of such structural colours with smart materials is
Externí odkaz:
http://arxiv.org/abs/2412.11705
Safe, smooth, and optimal motion planning for nonholonomically constrained mobile robots and autonomous vehicles is essential for achieving reliable, seamless, and efficient autonomy in logistics, mobility, and service industries. In many such applic
Externí odkaz:
http://arxiv.org/abs/2412.10350
In the current era of rapidly growing digital data, evaluating the political bias and factuality of news outlets has become more important for seeking reliable information online. In this work, we study the classification problem of profiling news me
Externí odkaz:
http://arxiv.org/abs/2412.10467
Autor:
Kabas, Bilal, Arslan, Fuat, Nezhad, Valiyeh A., Ozturk, Saban, Saritas, Emine U., Çukur, Tolga
Medical image reconstruction from undersampled acquisitions is an ill-posed problem that involves inversion of the imaging operator linking measurement and image domains. In recent years, physics-driven (PD) models have gained prominence in learning-
Externí odkaz:
http://arxiv.org/abs/2412.09331
Autor:
Latif, Imran, Newkirk, Alex C., Carbone, Matthew R., Munir, Arslan, Lin, Yuewei, Koomey, Jonathan, Yu, Xi, Dong, Zhiuha
The expansion of artificial intelligence (AI) applications has driven substantial investment in computational infrastructure, especially by cloud computing providers. Quantifying the energy footprint of this infrastructure requires models parameteriz
Externí odkaz:
http://arxiv.org/abs/2412.08602
We present an analytically solvable model based on the blast-wave picture of heavy-ion collisions with flow-momentum correspondence. It can describe the key features of spin polarizations in heavy-ion collisions. With the analytical solution, we can
Externí odkaz:
http://arxiv.org/abs/2411.17285
Autor:
Tselikov, Gleb, Minnekhanov, Anton, Ermolaev, Georgy, Tikhonowski, Gleb, Kazantsev, Ivan, Dyubo, Dmitry, Panova, Daria, Tselikov, Daniil, Popov, Anton, Mazitov, Arslan, Smirnov, Sergei, Lipilin, Fedor, Ahsan, Umer, Orekhov, Nikita, Kruglov, Ivan, Syuy, Alexander, Kabashin, Andrei, Chichkov, Boris, Sofer, Zdenek, Arsenin, Aleksey, Novoselov, Kostya, Volkov, Valentyn
Van der Waals (vdW) materials are becoming increasingly popular in scientific and industrial applications because of their unique mixture of record electronic, optical, and mechanical properties. However, nanostructuring of vdW materials is still in
Externí odkaz:
http://arxiv.org/abs/2411.14060
Autor:
Müller, Tom David, Siraj, Arslan, Walter, Axel, Kim, Jihyung, Wein, Samuel, von Kleist, Johannes, Feroz, Ayesha, Pilz, Matteo, Jeong, Kyowon, Sing, Justin Cyril, Charkow, Joshua, Röst, Hannes Luc, Sachsenberg, Timo
Liquid Chromatography Mass Spectrometry (LC-MS) is an indispensable analytical technique in proteomics, metabolomics, and other life sciences. While OpenMS provides advanced open-source software for MS data analysis, its complexity can be challenging
Externí odkaz:
http://arxiv.org/abs/2411.13189
Establishing the existence of exact or near Markov or stationary perfect Nash equilibria in nonzero-sum Markov games over Borel spaces remains a challenging problem, with few positive results to date. In this paper, we establish the existence of appr
Externí odkaz:
http://arxiv.org/abs/2411.10805