Zobrazeno 1 - 10
of 748 455
pro vyhledávání: '"Dennis, A"'
Autor:
Småbråten, Didrik R., Danmo, Frida H., Gaukås, Nikolai H., Singh, Sathya P., Kanas, Nikola, Meier, Dennis, Wiik, Kjell, Einarsrud, Mari-Ann, Selbach, Sverre M.
The family of hexagonal manganites is intensively studied for its multiferroicity, magnetoelectric coupling, improper ferroelectricity, functional domain walls, and topology-related scaling behaviors. It is established that these physical properties
Externí odkaz:
http://arxiv.org/abs/2411.00454
Autor:
Ochieng, Peter, Kaburu, Dennis
This paper presents a pilot study on direct speech-to-speech translation (S2ST) by leveraging linguistic similarities among selected African languages within the same phylum, particularly in cases where traditional data annotation is expensive or imp
Externí odkaz:
http://arxiv.org/abs/2410.23323
We study the optimal memorization capacity of modern Hopfield models and Kernelized Hopfield Models (KHMs), a transformer-compatible class of Dense Associative Memories. We present a tight analysis by establishing a connection between the memory conf
Externí odkaz:
http://arxiv.org/abs/2410.23126
Computational capability often falls short when confronted with massive data, posing a common challenge in establishing a statistical model or statistical inference method dealing with big data. While subsampling techniques have been extensively deve
Externí odkaz:
http://arxiv.org/abs/2410.22751
Autor:
Xi, Shaoke, Gao, Jiaqi, Liu, Mengqi, Cao, Jiamin, Li, Fuliang, Bu, Kai, Ren, Kui, Yu, Minlan, Cai, Dennis, Zhai, Ennan
With the growing performance requirements on networked applications, there is a new trend of offloading stateful network applications to SmartNICs to improve performance and reduce the total cost of ownership. However, offloading stateful network app
Externí odkaz:
http://arxiv.org/abs/2410.22229
Autor:
Zhang, Xi, Pu, Yuan, Kawamura, Yuki, Loza, Andrew, Bengio, Yoshua, Shung, Dennis L., Tong, Alexander
Modeling stochastic and irregularly sampled time series is a challenging problem found in a wide range of applications, especially in medicine. Neural stochastic differential equations (Neural SDEs) are an attractive modeling technique for this probl
Externí odkaz:
http://arxiv.org/abs/2410.21154
We study the awake complexity of graph problems that belong to the class O-LOCAL, which includes a large subset of problems solvable by sequential greedy algorithms, such as $(\Delta+1)$-coloring, maximal independent set, maximal matching, etc. It is
Externí odkaz:
http://arxiv.org/abs/2410.20499
In the past few years, a successful line of research has lead to lower bounds for several fundamental local graph problems in the distributed setting. These results were obtained via a technique called round elimination. On a high level, the round el
Externí odkaz:
http://arxiv.org/abs/2410.20224
Autor:
Sedighi, Nafise, Sharbaf, Zahra, Trujillo, Ignacio, Eskandarlou, Sepideh, Golini, Giulia, Infante-Sainz, Raúl, Raji, Samane, Zaritsky, Dennis, Ardakani, Pedram Ashofteh, Chamba, Nushkia, Shahisavandi, Zahra Hosseini, Donnerstein, Richard, D'Onofrio, Mauro, Martin, Garreth, Montes, Mireia, Román, Javier
With the arrival of the next generation of ultra-deep optical imaging surveys reaching $\mu_V$$\sim$30 mag/arcsec$^2$ (3$\sigma$; 10"$\times$10"), the removal of scattered light due to the point spread function (PSF) effect remains a critical step fo
Externí odkaz:
http://arxiv.org/abs/2410.20190
Autor:
MicroBooNE collaboration, Abratenko, P., Alterkait, O., Aldana, D. Andrade, Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barnard, A., Barr, G., Barrow, D., Barrow, J., Basque, V., Bateman, J., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhat, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Brunetti, M. B., Camilleri, L., Cao, Y., Caratelli, D., Cavanna, F., Cerati, G., Chappell, A., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Cross, R., Del Tutto, M., Dennis, S. R., Detje, P., Diurba, R., Djurcic, Z., Duffy, K., Dytman, S., Eberly, B., Englezos, P., Ereditato, A., Evans, J. J., Fang, C., Fleming, B. T., Foreman, W., Franco, D., Furmanski, A. P., Gao, F., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Gramellini, E., Green, P., Greenlee, H., Gu, L., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Handley, M. D., Hen, O., Hilgenberg, C., Horton-Smith, G. A., Imani, Z., Irwin, B., Ismail, M. S., James, C., Ji, X., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Lane, N., Li, J. -Y., Li, Y., Lin, K., Littlejohn, B. R., Liu, L., Louis, W. C., Luo, X., Mahmud, T., Mariani, C., Marsden, D., Marshall, J., Martinez, N., Caicedo, D. A. Martinez, Martynenko, S., Mastbaum, A., Mawby, I., McConkey, N., Meddage, V., Mellet, L., Mendez, J., Micallef, J., Miller, K., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Moudgalya, M. M., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nguyen, C., Nowak, J., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Pletcher, K., Pophale, I., Qian, X., Raaf, J. L., Radeka, V., Rafique, A., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., Safa, I., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Szelc, A. M., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Trettin, A., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Wang, J., Weber, M., Wei, H., White, A. J., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., Zhang, C.
Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle di
Externí odkaz:
http://arxiv.org/abs/2410.18419