Zobrazeno 1 - 10
of 73 959
pro vyhledávání: '"RAJESH, P."'
This paper presents the first-order supersymmetric rational extension of the quantum anisotropic harmonic oscillator (QAHO) in multiple dimensions, including full-line, half-line, and their combinations. The exact solutions are in terms of the except
Externí odkaz:
http://arxiv.org/abs/2411.02955
Autor:
Asapanna, Rajesh, Sokhen, Rabih El, Adiyatullin, Albert F., Hainaut, Clément, Delplace, Pierre, Gómez-León, Álvaro, Amo, Alberto
Discrete-step walks describe the dynamics of particles in a lattice subject to hopping or splitting events at discrete times. Despite being of primordial interest to the physics of quantum walks, the topological properties arising from their discrete
Externí odkaz:
http://arxiv.org/abs/2412.14324
For correlators in $\mathcal{N}=4$ Super Yang-Mills preserving half the supersymmetry, we manifestly recast the gauge theory Feynman diagram expansion as a sum over dual closed strings. Each individual Feynman diagram maps on to a Riemann surface wit
Externí odkaz:
http://arxiv.org/abs/2412.13397
Autor:
Ling, Jianheng, Worah, Pratik, Wang, Yawen, Kong, Yunchuan, Wang, Chunlei, Stein, Clifford, Gupta, Diwakar, Behmer, Jason, Bush, Logan A., Ramanan, Prakash, Kumar, Rajesh, Chestna, Thomas, Liu, Yajing, Liu, Ying, Zhao, Ye, McKinley, Kathryn S., Park, Meeyoung, Maas, Martin
Scheduling virtual machines (VMs) to hosts in cloud data centers dictates efficiency and is an NP-hard problem with incomplete information. Prior work improved VM scheduling with predicted VM lifetimes. Our work further improves lifetime-aware schedu
Externí odkaz:
http://arxiv.org/abs/2412.09840
Autor:
Grytsenko, Ivan, van Haagen, Sander, Rybalko, Oleksiy, Jennings, Asher, Mohan, Rajesh, Tian, Yiran, Kawakami, Erika
We developed a tunnel diode oscillator and characterized its performance, highlighting its potential applications in the quantum state readout of electrons insemiconductors and electrons on liquid helium. This cryogenic microwave source demonstrates
Externí odkaz:
http://arxiv.org/abs/2412.09811
Autor:
Hu, Dongting, Chen, Jierun, Huang, Xijie, Coskun, Huseyin, Sahni, Arpit, Gupta, Aarush, Goyal, Anujraaj, Lahiri, Dishani, Singh, Rajesh, Idelbayev, Yerlan, Cao, Junli, Li, Yanyu, Cheng, Kwang-Ting, Chan, S. -H. Gary, Gong, Mingming, Tulyakov, Sergey, Kag, Anil, Xu, Yanwu, Ren, Jian
Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to address all of these challenges by developing an extremely small and f
Externí odkaz:
http://arxiv.org/abs/2412.09619
Autor:
Han, Gyeo-Re, Goncharov, Artem, Eryilmaz, Merve, Ye, Shun, Joung, Hyou-Arm, Ghosh, Rajesh, Ngo, Emily, Tomoeda, Aoi, Lee, Yena, Ngo, Kevin, Melton, Elizabeth, Garner, Omai B., Di Carlo, Dino, Ozcan, Aydogan
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, we demonstrate high-sensitivity detection of cardiac troponin I (cTnI) through innovations
Externí odkaz:
http://arxiv.org/abs/2412.08945
This paper explores hate speech detection in Devanagari-scripted languages, focusing on Hindi and Nepali, for Subtask B of the CHIPSAL@COLING 2025 Shared Task. Using a range of transformer-based models such as XLM-RoBERTa, MURIL, and IndicBERT, we ex
Externí odkaz:
http://arxiv.org/abs/2412.08163
Autor:
Kannan, Kamala Devi, Jagatheesaperumal, Senthil Kumar, Kandala, Rajesh N. V. P. S., Lotfaliany, Mojtaba, Alizadehsanid, Roohallah, Mohebbi, Mohammadreza
For the early identification, diagnosis, and treatment of mental health illnesses, the integration of deep learning (DL) and machine learning (ML) has started playing a significant role. By evaluating complex data from imaging, genetics, and behavior
Externí odkaz:
http://arxiv.org/abs/2412.06147
We propose a novel approach to learn relational policies for classical planning based on learning to rank actions. We introduce a new graph representation that explicitly captures action information and propose a Graph Neural Network architecture aug
Externí odkaz:
http://arxiv.org/abs/2412.04752