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pro vyhledávání: '"SINGH, AMIT"'
Deep learning and advancements in contactless sensors have significantly enhanced our ability to understand complex human activities in healthcare settings. In particular, deep learning models utilizing computer vision have been developed to enable d
Externí odkaz:
http://arxiv.org/abs/2410.09339
Autor:
Abhikeern, Kunwar, Singh, Amit
Using spectral energy density method, we predict the phonon scattering mean lifetimes of polycrystalline graphene (PC-G) having polycrystallinity only along $\rm{x}$-axis with seven different misorientation (tilt) angles at room temperature. Contrary
Externí odkaz:
http://arxiv.org/abs/2409.04503
In this note, we continue the study of Seshadri constants on blow-ups of Hirzebruch surfaces initiated in arXiv:2312.14555. Now we consider blow-ups of ruled surfaces more generally. We propose a conjecture for classifying all the negative self-inter
Externí odkaz:
http://arxiv.org/abs/2407.18678
Accurately retrieving relevant bid keywords for user queries is critical in Sponsored Search but remains challenging, particularly for short, ambiguous queries. Existing dense and generative retrieval models often fail to capture nuanced user intent
Externí odkaz:
http://arxiv.org/abs/2407.14346
Autor:
Bañuls, Mari Carmen, Cichy, Krzysztof, Hung, Hao-Ti, Kao, Ying-Jer, Lin, C. -J. David, Singh, Amit
Using tensor network methods, we simulate the real-time evolution of the lattice Thirring model quenched out of equilibrium in both the critical and massive phases, and study the appearance of dynamical quantum phase transitions, as non-analyticities
Externí odkaz:
http://arxiv.org/abs/2407.11295
Emerging microstructural characterization methods have received increased attention owing to their promise of relatively inexpensive and rapid measurement of polycrystalline surface morphology and crystallographic orientations. Among these nascent me
Externí odkaz:
http://arxiv.org/abs/2406.20014
Autor:
Valluri, Ravisri, Mohankumar, Akash Kumar, Dave, Kushal, Singh, Amit, Jiao, Jian, Varma, Manik, Sinha, Gaurav
Generative Retrieval introduces a new approach to Information Retrieval by reframing it as a constrained generation task, leveraging recent advancements in Autoregressive (AR) language models. However, AR-based Generative Retrieval methods suffer fro
Externí odkaz:
http://arxiv.org/abs/2406.06739
Autor:
Kumar, Dayanand, Li, Hanrui, Singh, Amit, Rajbhar, Manoj Kumar, Syed, Abdul Momin, Lee, Hoonkyung, El-Atab, Nazek
Photoresponsivity studies of wide-bandgap oxide-based devices have emerged as a vibrant and popular research area. Researchers have explored various material systems in their quest to develop devices capable of responding to illumination. In this stu
Externí odkaz:
http://arxiv.org/abs/2404.05701
Publikováno v:
RSC Adv., 2019, 9, 40309-40315
First-principle calculations were employed to analyze the effects induced by vacancies of molybdenum (Mo) and sulfur (S) on the dielectric properties of few-layered MoS2. We explored the combined effects of vacancies and dipole interactions on the di
Externí odkaz:
http://arxiv.org/abs/2403.11140
Traffic congestion is one of the major issues in urban areas, particularly when traffic loads exceed the roads capacity, resulting in higher petrol consumption and carbon emissions as well as delays and stress for road users. In Asia, the traffic sit
Externí odkaz:
http://arxiv.org/abs/2403.09023