Zobrazeno 1 - 10
of 33 819
pro vyhledávání: '"A, Meehan"'
Autor:
Bai, Yuehao, Tabord-Meehan, Max
This paper studies the sharp testable implications of an additive random utility model with a discrete multi-valued treatment and a discrete multi-valued instrument, in which each value of the instrument only weakly increases the utility of one choic
Externí odkaz:
http://arxiv.org/abs/2411.09808
Robot manipulation in real-world settings often requires adapting the robot's behavior to the current situation, such as by changing the sequences in which policies execute to achieve the desired task. Problematically, however, we show that composing
Externí odkaz:
http://arxiv.org/abs/2409.08195
Autor:
Maouloud, Sid El Moctar Ahmed, Nguyen, Anh, Liu, XinRan, Dobson, James Edward Young, Ghag, Chamkaur, Floch, Léna Le, Meehan, Emma, Murphy, Alexander St. John, Paling, Sean Michael, Saakyan, Ruben, Scovell, Paul Robert, Toth, Christopher
The Boulby UnderGround Screening (BUGS) facility, located at the Boulby Underground Laboratory, has significantly advanced its material screening capabilities by installing two XIA UltraLo-1800 alpha particle detectors. This study presents a comprehe
Externí odkaz:
http://arxiv.org/abs/2408.06925
Many organizations use algorithms that have a disparate impact, i.e., the benefits or harms of the algorithm fall disproportionately on certain social groups. Addressing an algorithm's disparate impact can be challenging, however, because it is often
Externí odkaz:
http://arxiv.org/abs/2405.04816
The past two decades have witnessed a surge of new research in the analysis of randomized experiments. The emergence of this literature may seem surprising given the widespread use and long history of experiments as the "gold standard" in program eva
Externí odkaz:
http://arxiv.org/abs/2405.03910
Autor:
Abe, K., Bronner, C., Hayato, Y., Hiraide, K., Hosokawa, K., Ieki, K., Ikeda, M., Kameda, J., Kanemura, Y., Kaneshima, R., Kashiwagi, Y., Kataoka, Y., Miki, S., Mine, S., Miura, M., Moriyama, S., Nakano, Y., Nakahata, M., Nakayama, S., Noguchi, Y., Sato, K., Sekiya, H., Shiba, H., Shimizu, K., Shiozawa, M., Sonoda, Y., Suzuki, Y., Takeda, A., Takemoto, Y., Tanaka, H., Yano, T., Han, S., Kajita, T., Okumura, K., Tashiro, T., Tomiya, T., Wang, X., Yoshida, S., Fernandez, P., Labarga, L., Ospina, N., Zaldivar, B., Pointon, B. W., Kearns, E., Raaf, J. L., Wan, L., Wester, T., Bian, J., Griskevich, N. J., Smy, M. B., Sobel, H. W., Takhistov, V., Yankelevich, A., Hill, J., Jang, M. C., Lee, S. H., Moon, D. H., Park, R. G., Bodur, B., Scholberg, K., Walter, C. W., Beauchene, A., Drapier, O., Giampaolo, A., Mueller, Th. A., Santos, A. D., Paganini, P., Quilain, B., Rogly, R., Nakamura, T., Jang, J. S., Machado, L. N., Learned, J. G., Choi, K., Iovine, N., Cao, S., Anthony, L. H. V., Martin, D., Prouse, N. W., Scott, M., Uchida, Y., Berardi, V., Calabria, N. F., Catanesi, M. G., Radicioni, E., Langella, A., De Rosa, G., Collazuol, G., Iacob, F., Mattiazzi, M., Ludovici, L., Gonin, M., Perisse, L., Pronost, G., Fujisawa, C., Maekawa, Y., Nishimura, Y., Okazaki, R., Akutsu, R., Friend, M., Hasegawa, T., Ishida, T., Kobayashi, T., Jakkapu, M., Matsubara, T., Nakadaira, T., Nakamura, K., Oyama, Y., Sakashita, K., Sekiguchi, T., Tsukamoto, T., Bhuiyan, N., Burton, G. T., Di Lodovico, F., Gao, J., Goldsack, A., Katori, T., Migenda, J., Ramsden, R. M., Xie, Z., Zsoldos, S., Suzuki, A. T., Takagi, Y., Takeuchi, Y., Zhong, H., Feng, J., Feng, L., Hu, J. R., Hu, Z., Kawaue, M., Kikawa, T., Mori, M., Nakaya, T., Wendell, R. A., Yasutome, K., Jenkins, S. J., McCauley, N., Mehta, P., Tarant, A., Wilking, M. J., Fukuda, Y., Itow, Y., Menjo, H., Ninomiya, K., Yoshioka, Y., Lagoda, J., Mandal, M., Mijakowski, P., Prabhu, Y. S., Zalipska, J., Jia, M., Jiang, J., Shi, W., Yanagisawa, C., Harada, M., Hino, Y., Ishino, H., Koshio, Y., Nakanishi, F., Sakai, S., Tada, T., Tano, T., Ishizuka, T., Barr, G., Barrow, D., Cook, L., Samani, S., Wark, D., Holin, A., Nova, F., Jung, S., Yang, B. S., Yang, J. Y., Yoo, J., Fannon, J. E. P., Kneale, L., Malek, M., McElwee, J. M., Thiesse, M. D., Thompson, L. F., Wilson, S. T., Okazawa, H., Lakshmi, S. M., Kim, S. B., Kwon, E., Seo, J. W., Yu, I., Ichikawa, A. K., Tairafune, S., Nishijima, K., Eguchi, A., Nakagiri, K., Nakajima, Y., Shima, S., Taniuchi, N., Watanabe, E., Yokoyama, M., de Perio, P., Fujita, S., Jesus-Valls, C., Martens, K., Tsui, K. M., Vagins, M. R., Xia, J., Izumiyama, S., Kuze, M., Matsumoto, R., Terada, K., Ishitsuka, M., Ito, H., Ommura, Y., Shigeta, N., Shinoki, M., Yamauchi, K., Yoshida, T., Gaur, R., Gousy-Leblanc, V., Hartz, M., Konaka, A., Li, X., Chen, S., Xu, B. D., Zhang, B., Posiadala-Zezula, M., Boyd, S. B., Edwards, R., Hadley, D., Nicholson, M., O'Flaherty, M., Richards, B., Ali, A., Jamieson, B., Amanai, S., Marti, Ll., Minamino, A., Suzuki, S., Scovell, P. R., Meehan, E., Bandac, I., Pena-Garay, C., Perez, J., Gileva, O., Lee, E. K., Leonard, D. S., Sakakieda, Y., Sakaguchi, A., Sueki, K., Takaku, Y., Yamasaki, S.
Publikováno v:
Nuclear Inst. and Methods in Physics Research, A 1065 (2024) 169480
The first loading of gadolinium (Gd) into Super-Kamiokande in 2020 was successful, and the neutron capture efficiency on Gd reached 50\%. To further increase the Gd neutron capture efficiency to 75\%, 26.1 tons of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O
Externí odkaz:
http://arxiv.org/abs/2403.07796
We introduce Double Cost Volume Stereo Matching Network(DCVSMNet) which is a novel architecture characterised by by two small upper (group-wise) and lower (norm correlation) cost volumes. Each cost volume is processed separately, and a coupling modul
Externí odkaz:
http://arxiv.org/abs/2402.16473
Statistics about traffic flow and people's movement gathered from multiple geographical locations in a distributed manner are the driving force powering many applications, such as traffic prediction, demand prediction, and restaurant occupancy report
Externí odkaz:
http://arxiv.org/abs/2402.11526
We thank Savje (2023) for a thought-provoking article and appreciate the opportunity to share our perspective as social scientists. In his article, Savje recommends misspecified exposure effects as a way to avoid strong assumptions about interference
Externí odkaz:
http://arxiv.org/abs/2401.06264
Node2vec is a graph embedding method that learns a vector representation for each node of a weighted graph while seeking to preserve relative proximity and global structure. Numerical experiments suggest Node2vec struggles to recreate the topology of
Externí odkaz:
http://arxiv.org/abs/2309.08241