Zobrazeno 1 - 10
of 12 573
pro vyhledávání: '"Mohebbi, A."'
In recent years, the integration of advanced imaging techniques and deep learning methods has significantly advanced computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Transformers, which have shown great promise i
Externí odkaz:
http://arxiv.org/abs/2410.19166
Transformer-based language models have shown an excellent ability to effectively capture and utilize contextual information. Although various analysis techniques have been used to quantify and trace the contribution of single contextual cues to a tar
Externí odkaz:
http://arxiv.org/abs/2410.03447
Neural speech models build deeply entangled internal representations, which capture a variety of features (e.g., fundamental frequency, loudness, syntactic category, or semantic content of a word) in a distributed encoding. This complexity makes it d
Externí odkaz:
http://arxiv.org/abs/2410.03037
Drones are increasingly used in fields like industry, medicine, research, disaster relief, defense, and security. Technical challenges, such as navigation in GPS-denied environments, hinder further adoption. Research in visual odometry is advancing,
Externí odkaz:
http://arxiv.org/abs/2404.17745
Hydrodynamic interactions among swimming or flying organisms can lead to complex flows on the scale of the group. These emergent fluid dynamics are often more complex than a linear superposition of individual organism flows, especially at intermediat
Externí odkaz:
http://arxiv.org/abs/2403.08973
Autor:
Mazzone, Giusy, Mohebbi, Mahdi
We consider a mass-spring system immersed in an incompressible fluid flow governed by the Navier-Stokes equations subject to a prescribed time-periodic flow rate (and possibly external time-periodic body forces on the fluid and the mass). We show tha
Externí odkaz:
http://arxiv.org/abs/2312.08690
Autor:
Najmabadi, B. Mohebbi, Shateri, T. L.
In this paper, we give some requirements under which two self-mappings have a common fixed point in $b$-metric-like spaces.
Externí odkaz:
http://arxiv.org/abs/2312.03714
Transformers have become a key architecture in speech processing, but our understanding of how they build up representations of acoustic and linguistic structure is limited. In this study, we address this gap by investigating how measures of 'context
Externí odkaz:
http://arxiv.org/abs/2310.09925
In recent years, many interpretability methods have been proposed to help interpret the internal states of Transformer-models, at different levels of precision and complexity. Here, to analyze encoder-decoder Transformers, we propose a simple, new me
Externí odkaz:
http://arxiv.org/abs/2310.03686
Autor:
Munteanu, Viorel, Saldana, Michael, Ciorba, Dumitru, Bostan, Viorel, Su, Justin Maine, Kasianchuk, Nadiia, Sharma, Nitesh Kumar, Knyazev, Sergey, Gordeev, Victor, Aßmann, Eva, Lobiuc, Andrei, Covasa, Mihai, Crandall, Keith A., Ouyang, Wenhao O., Wu, Nicholas C., Mason, Christopher, Tierney, Braden T, Lucaci, Alexander G, Zelikovsky, Alex, Mohebbi, Fatemeh, Skums, Pavel, Gibas, Cynthia, Schlueter, Jessica, Rzymski, Piotr, Solo-Gabriele, Helena, Hölzer, Martin, Smith, Adam, Mangul, Serghei
During the SARS-CoV-2 pandemic, wastewater-based genomic surveillance (WWGS) emerged as an efficient viral surveillance tool that takes into account asymptomatic cases and can identify known and novel mutations and offers the opportunity to assign kn
Externí odkaz:
http://arxiv.org/abs/2309.13326