Zobrazeno 1 - 10
of 8 229
pro vyhledávání: '"Naeini, A."'
Autor:
Haghshenas, Seyed Hamed, Naeini, Mia
State Estimation is a crucial task in power systems. Graph Neural Networks have demonstrated significant potential in state estimation for power systems by effectively analyzing measurement data and capturing the complex interactions and interrelatio
Externí odkaz:
http://arxiv.org/abs/2410.16008
Coastal regions in North America face major threats from storm surges caused by hurricanes and nor'easters. Traditional numerical models, while accurate, are computationally expensive, limiting their practicality for real-time predictions. Recently,
Externí odkaz:
http://arxiv.org/abs/2410.12823
Autor:
Haghighi, Yasaman, Demonsant, Celine, Chalimourdas, Panagiotis, Naeini, Maryam Tavasoli, Munoz, Jhon Kevin, Bacca, Bladimir, Suter, Silvan, Gani, Matthieu, Alahi, Alexandre
In this paper, we introduce HEADS-UP, the first egocentric dataset collected from head-mounted cameras, designed specifically for trajectory prediction in blind assistance systems. With the growing population of blind and visually impaired individual
Externí odkaz:
http://arxiv.org/abs/2409.20324
Autor:
Lonbar, Ahmad Gholizadeh, Hasanzadeh, Hamidreza, Asgari, Fahimeh, Naeini, Hajar Kazemi, Shomali, Roya, Asadi, Saeed
The proliferation of complex online media has accelerated the process of ideology formation, influenced by stakeholders through advertising channels. The media channels, which vary in cost and effectiveness, present a dilemma in prioritizing optimal
Externí odkaz:
http://arxiv.org/abs/2409.18976
Autor:
Rajabzadeh, Taha, Boulton-McKeehan, Alex, Bonkowsky, Sam, Schuster, David I., Safavi-Naeini, Amir H.
Engineering the Hamiltonian of a quantum system is fundamental to the design of quantum systems. Automating Hamiltonian design through gradient-based optimization can dramatically accelerate this process. However, computing the gradients of eigenvalu
Externí odkaz:
http://arxiv.org/abs/2408.12704
We propose networking superconducting quantum circuits by transducing their excitations (typically 4-8 GHz) to 100-500 MHz photons for transmission via cryogenic coaxial cables. Counter-intuitively, this frequency downconversion reduces noise and tra
Externí odkaz:
http://arxiv.org/abs/2407.20943
Accurate assessment of myocardial tissue stiffness is pivotal for the diagnosis and prognosis of heart diseases. Left ventricular diastolic stiffness ($\beta$) obtained from the end-diastolic pressure-volume relationship (EDPVR) has conventionally be
Externí odkaz:
http://arxiv.org/abs/2407.15254
Photonic addressing of superconducting circuits has been proposed to overcome wiring complexity and heat load challenges, but superconducting-photonic links suffer from an efficiency-noise trade-off that limits scalability. This trade-off arises beca
Externí odkaz:
http://arxiv.org/abs/2406.14501
Autor:
Mayor, Felix M., Malik, Sultan, Primo, André G., Gyger, Samuel, Jiang, Wentao, Alegre, Thiago P. M., Safavi-Naeini, Amir H.
Integrated optomechanical systems are one of the leading platforms for manipulating, sensing, and distributing quantum information. The temperature increase due to residual optical absorption sets the ultimate limit on performance for these applicati
Externí odkaz:
http://arxiv.org/abs/2406.14484
Autor:
Waqas, Asim, Tripathi, Aakash, Stewart, Paul, Naeini, Mia, Schabath, Matthew B., Rasool, Ghulam
Cancer clinics capture disease data at various scales, from genetic to organ level. Current bioinformatic methods struggle to handle the heterogeneous nature of this data, especially with missing modalities. We propose PARADIGM, a Graph Neural Networ
Externí odkaz:
http://arxiv.org/abs/2406.08521