Zobrazeno 1 - 10
of 21 100
pro vyhledávání: '"Fogel AS"'
Autor:
Abramovich, Ofir, Nayman, Niv, Fogel, Sharon, Lavi, Inbal, Litman, Ron, Tsiper, Shahar, Tichauer, Royee, Appalaraju, Srikar, Mazor, Shai, Manmatha, R.
In recent years, notable advancements have been made in the domain of visual document understanding, with the prevailing architecture comprising a cascade of vision and language models. The text component can either be extracted explicitly with the u
Externí odkaz:
http://arxiv.org/abs/2407.12594
Autor:
Fogel, Fajwel, Perron, Yohann, Besic, Nikola, Saint-André, Laurent, Pellissier-Tanon, Agnès, Schwartz, Martin, Boudras, Thomas, Fayad, Ibrahim, d'Aspremont, Alexandre, Landrieu, Loic, Ciais, Philippe
Estimating canopy height and canopy height change at meter resolution from satellite imagery has numerous applications, such as monitoring forest health, logging activities, wood resources, and carbon stocks. However, many existing forest datasets ar
Externí odkaz:
http://arxiv.org/abs/2407.09392
Autor:
Fogel, Jamie, Modenesi, Bernardo
Recent advances in the literature of decomposition methods in economics have allowed for the identification and estimation of detailed wage gap decompositions. In this context, building reliable counterfactuals requires using tighter controls to ensu
Externí odkaz:
http://arxiv.org/abs/2405.04365
Autor:
Adiyeke, Esra, Ren, Yuanfang, Fogel, Shmuel, Rashidi, Parisa, Segal, Mark, Shenkman, Elizabeth A., Bihorac, Azra, Ozrazgat-Baslanti, Tezcan
Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost one fifth of hospitalized patients, as well as more than half of the patients who are admitted to the intensive care unit (ICU). Stratifying AKI patients into groups based
Externí odkaz:
http://arxiv.org/abs/2403.08020
Autor:
Belle Collaboration, Nayak, M., Dey, S., Soffer, A., Adachi, I., Aihara, H., Said, S. Al, Asner, D. M., Atmacan, H., Ayad, R., Babu, V., Banerjee, Sw., Bauer, M., Behera, P., Belous, K., Bessner, M., Bhardwaj, V., Bhuyan, B., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Campajola, M., Červenkov, D., Chang, M. -C., Cheon, B. G., Cho, H. E., Cho, K., Choi, Y., Choudhury, S., Das, S., De Nardo, G., De Pietro, G., Dhamija, R., Di Capua, F., Dingfelder, J., Doležal, Z., Dong, T. V., Dubey, S., Ecker, P., Epifanov, D., Ferber, T., Fogel, O., Fulsom, B. G., Gaur, V., Giri, A., Goldenzweig, P., Graziani, E., Gudkova, K., Hadjivasiliou, C., Halder, S., Hara, T., Hayasaka, K., Hayashii, H., Hazra, S., Hedges, M. T., Herrmann, D., Hou, W. -S., Hsu, C. -L., Inami, K., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobs, W. W., Jia, S., Jin, Y., Kawasaki, T., Kiesling, C., Kim, C. H., Kim, D. Y., Kinoshita, K., Kodyš, P., Korobov, A., Korpar, S., Križan, P., Krokovny, P., Kuhr, T., Kumar, D., Kumar, R., Kuzmin, A., Kwon, Y. -J., Lai, Y. -T., Lam, T., Lange, J. S., Laurenza, M., Lee, S. C., Li, L. K., Li, Y. B., Gioi, L. Li, Libby, J., Lieret, K., Lin, Y. -R., Liventsev, D., Luo, T., Ma, Y., Masuda, M., Maurya, S. K., Meier, F., Merola, M., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Mussa, R., Nakamura, I., Nakao, M., Natkaniec, Z., Natochii, A., Nayak, L., Nishida, S., Ogawa, S., Ono, H., Oskin, P., Pakhlov, P., Pakhlova, G., Pardi, S., Park, H., Park, J., Park, S. -H., Passeri, A., Patra, S., Paul, S., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Röhrken, M., Rostomyan, A., Rout, N., Russo, G., Sandilya, S., Santelj, L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Sevior, M. E., Shan, W., Sharma, C., Shen, C. P., Shiu, J. -G., Singh, J. B., Sokolov, A., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tanida, K., Tenchini, F., Unno, Y., Uno, S., Ushiroda, Y., Vahsen, S. E., Wang, M. -Z., Watanuki, S., Won, E., Yabsley, B. D., Yan, W., Yin, J. H., Yuan, L., Zhang, Z. P., Zhilich, V., Zhukova, V.
Publikováno v:
Phys.Rev.D 109 (2024) 11, L111102
We report a search for a heavy neutral lepton (HNL) that mixes predominantly with $\nu_\tau$. The search utilizes data collected with the Belle detector at the KEKB asymmetric energy $e^+ e^-$ collider. The data sample was collected at and just below
Externí odkaz:
http://arxiv.org/abs/2402.02580
Autor:
Blau, Tsachi, Fogel, Sharon, Ronen, Roi, Golts, Alona, Ganz, Roy, Avraham, Elad Ben, Aberdam, Aviad, Tsiper, Shahar, Litman, Ron
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA), leading methods focus on the single-page setting, while documents can span hundre
Externí odkaz:
http://arxiv.org/abs/2401.03411
Autor:
Fogel, Jamie, Modenesi, Bernardo
This paper develops a new data-driven approach to characterizing latent worker skill and job task heterogeneity by applying an empirical tool from network theory to large-scale Brazilian administrative data on worker--job matching. We microfound this
Externí odkaz:
http://arxiv.org/abs/2311.00777
Autor:
Noa Zifman, Ofri Levy-Lamdan, Tal Hiller, Avner Thaler, Iftach Dolev, Anat Mirelman, Hilla Fogel, Mark Hallett, Inbal Maidan
Publikováno v:
npj Parkinson's Disease, Vol 10, Iss 1, Pp 1-9 (2024)
Abstract Distinguishing Parkinson’s disease (PD) subgroups may be achieved by observing network responses to external stimuli. We compared TMS-evoked potential (TEP) measures from stimulation of bilateral motor cortex (M1), dorsolateral prefrontal
Externí odkaz:
https://doaj.org/article/37c1fe22d16c4bd0bcd446b41a5ab313
Autor:
Chu, Ling1 (AUTHOR), Fogel-Yaari, Hila2 (AUTHOR) hila.fogelyaari@uta.edu, Zhang, Ping3 (AUTHOR)
Publikováno v:
Journal of Accounting, Auditing & Finance. Apr2024, Vol. 39 Issue 2, p589-613. 25p.
Autor:
Yao, Tina, Clair, Nicole St., Miller, Gabriel F., Dorfman, Adam L., Fogel, Mark A., Ghelani, Sunil, Krishnamurthy, Rajesh, Lam, Christopher Z., Robinson, Joshua D., Schidlow, David, Slesnick, Timothy C., Weigand, Justin, Quail, Michael, Rathod, Rahul, Steeden, Jennifer A., Muthurangu, Vivek
Purpose: To develop and evaluate an end-to-end deep learning pipeline for segmentation and analysis of cardiac magnetic resonance images to provide core-lab processing for a multi-centre registry of Fontan patients. Materials and Methods: This retros
Externí odkaz:
http://arxiv.org/abs/2303.11676