Zobrazeno 1 - 10
of 6 346
pro vyhledávání: '"Saberi, P"'
Deep learning (DL) methods, especially those based on physics-driven DL, have become the state-of-the-art for reconstructing sub-sampled magnetic resonance imaging (MRI) data. However, studies have shown that these methods are susceptible to small ad
Externí odkaz:
http://arxiv.org/abs/2501.01908
Autor:
Abdollahi, Mahdi, Aghdam, Sima Taefi, Javadi, Atefeh, Hashemi, Seyed Azim, van Loon, Jacco Th., Khosroshahi, Habib, Golshan, Roya Hamedani, Saremi, Elham, Saberi, Maryam
NGC 5128 (Centaurus A), the closest giant elliptical galaxy outside the Local Group to the Milky Way, is one of the brightest extragalactic radio sources. It is distinguished by a prominent dust lane and powerful jets, driven by a supermassive black
Externí odkaz:
http://arxiv.org/abs/2412.05642
Autor:
Saberi, Maryam, Jafarzadeh, Shahin, Wedemeyer, Sven, Gafeira, Ricardo, Szydlarski, Mikolaj, Jess, David, Stangalini, Marco
Publikováno v:
A&A 693, A19 (2025)
Magnetohydrodynamic (MHD) waves, playing a crucial role in transporting energy through the solar atmosphere, manifest in various chromospheric structures. Here, we investigated MHD waves in a long-lasting dark fibril using high-temporal-resolution (2
Externí odkaz:
http://arxiv.org/abs/2411.14190
In this paper, we propose a new framework for synchronization of heterogeneous multi agent system which we refer to as weak synchronization. This new framework of synchronization is based on achieving the network stability in the absence of any infor
Externí odkaz:
http://arxiv.org/abs/2411.13806
Autor:
Cooke, D. A., Pannell, F., Della Porta, G. Zevi, Farmer, J., Bencini, V., Bergamaschi, M., Mazzoni, S., Ranc, L., Senes, E., Sherwood, P., Wing, M., Agnello, R., Ahdida, C. C., Amoedo, C., Andrebe, Y., Apsimon, O., Apsimon, R., Arnesano, J. M., Blanchard, P., Burrows, P. N., Buttenschön, B., Caldwell, A., Chung, M., Clairembaud, A., Davut, C., Demeter, G., Dexter, A. C., Doebert, S., Fasoli, A., Fonseca, R., Furno, I., van Gils, N. Z., Granados, E., Granetzny, M., Graubner, T., Grulke, O., Gschwendtner, E., Guran, E., Henderson, J., Kedves, M. Á., Kraus, F., Krupa, M., Lefevre, T., Liang, L., Liu, S., Lopes, N., Lotov, K., Calderon, M. Martinez, Mezger, J., Guzmán, P. I. Morales, Moreira, M., Nechaeva, T., Okhotnikov, N., Pakuza, C., Pardons, A., Pepitone, K., Poimendidou, E., Pucek, J., Pukhov, A., Ramjiawan, R. L., Rey, S., Rossel, R., Saberi, H., Schmitz, O., Silva, F., Silva, L., Spear, B., Stollberg, C., Sublet, A., Swain, C., Topaloudis, A., Tuev, N. TorradoP., Velotti, F., Verzilov, V., Vieira, J., Walter, E., Welsch, C., Wendt, M., Wolfenden, J., Woolley, B., Xia, G., Verra, L., Yarygova, V., Zepp, M.
The vertical plane transverse emittance of accelerated electron bunches at the AWAKE experiment at CERN has been determined, using three different methods of data analysis. This is a proof-of-principle measurement using the existing AWAKE electron sp
Externí odkaz:
http://arxiv.org/abs/2411.08681
We study stationary online bipartite matching, where both types of nodes--offline and online--arrive according to Poisson processes. Offline nodes wait to be matched for some random time, determined by an exponential distribution, while online nodes
Externí odkaz:
http://arxiv.org/abs/2411.08218
Autor:
Saberi, Amir Hossein, Najafi, Amir, Emrani, Ala, Behjati, Amin, Zolfimoselo, Yasaman, Shadrooy, Mahdi, Motahari, Abolfazl, Khalaj, Babak H.
The aim of this paper is to address the challenge of gradual domain adaptation within a class of manifold-constrained data distributions. In particular, we consider a sequence of $T\ge2$ data distributions $P_1,\ldots,P_T$ undergoing a gradual shift,
Externí odkaz:
http://arxiv.org/abs/2410.14061
Autor:
Ahmadi, Sahar, Cheraghian, Ali, Saberi, Morteza, Abir, Md. Towsif, Dastmalchi, Hamidreza, Hussain, Farookh, Rahman, Shafin
Recent advances in deep learning for processing point clouds hold increased interest in Few-Shot Class Incremental Learning (FSCIL) for 3D computer vision. This paper introduces a new method to tackle the Few-Shot Continual Incremental Learning (FSCI
Externí odkaz:
http://arxiv.org/abs/2410.09237
Accurate bicycling volume estimation is crucial for making informed decisions about future investments in bicycling infrastructure. Traditional link-level volume estimation models are effective for motorised traffic but face significant challenges wh
Externí odkaz:
http://arxiv.org/abs/2410.08522
Given a supermanifold equipped with an odd distribution of maximal dimension and constant symbol, we construct the formal moduli problem of deformations of the distribution. This moduli problem is described by a local super dg Lie algebra that provid
Externí odkaz:
http://arxiv.org/abs/2410.08176