Zobrazeno 1 - 10
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pro vyhledávání: '"An LK"'
Multi-agent reinforcement learning (MARL) methods struggle with the non-stationarity of multi-agent systems and fail to adaptively learn online when tested with novel agents. Here, we leverage large language models (LLMs) to create an autonomous agen
Externí odkaz:
http://arxiv.org/abs/2407.07086
Autor:
Belle Collaboration, Maity, S., Garg, R., Bahinipati, S., Bhardwaj, V., Aihara, H., Said, S. Al, Asner, DM, Atmacan, H., Aushev, T., Ayad, R., Babu, V., Banerjee, Sw., Bauer, M., Bennett, J., Bessner, M., Biswas, D., Bobrov, A., Bodrov, D., Bonvicini, G., Borah, J., Bračko, M., Branchini, P., Budano, A., Campajola, M., Červenkov, D., Chang, M. -C., Chang, P., Chilikin, K., Cho, H. E., Cho, K., Cho, S. -J., Choi, S. -K., Choi, Y., Choudhury, S., Das, S., Dash, N., De Pietro, G., Dhamija, R., Di Capua, F., Dingfelder, J., Dong, TV, Ecker, P., Epifanov, D., Ferber, T., Fulsom, BG, Gaur, V., Giri, A., Goldenzweig, P., Graziani, E., Gu, T., Gudkova, K., Hadjivasiliou, C., Hayasaka, K., Hayashii, H., Hazra, S., Hou, W. -S., Hsu, C. -L., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobs, WW, Jin, Y., Kalita, D., Kiesling, C., Kim, CH, Kim, DY, Kinoshita, K., }, P. Kody\v{s, Korobov, A., Korpar, S., Križan, P., Krokovny, P., Kumar, M., Kumar, R., Kumara, K., Kuzmin, A., Kwon, Y. -J., Lam, T., Lee, SC, Levit, D., Li, LK, Li, Y., Li, YB, Gioi, L. Li, Lieret, K., Liventsev, D., Masuda, M., Matsuda, T., Matvienko, D., Maurya, SK, Meier, F., Merola, M., Metzner, F., Mizuk, R., Mohanty, G. B., Mussa, R., Nakao, M., Narwal, D., Natochii, A., Nayak, L., Nishida, S., Ogawa, S., Ono, H., Oskin, P., Pakhlova, G., Pardi, S., Park, H., Park, J., Park, S. -H., Passeri, A., Patra, S., Paul, S., Pedlar, TK, Pestotnik, R., Piilonen, LE, Podobnik, T., Prell, S., Prencipe, E., Prim, MT, Rout, N., Russo, G., Sakai, Y., Sandilya, S., Santelj., L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Shan, W., Sharma, C., Shiu, J. -G., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tanida, K., Tenchini, F., Trabelsi, K., Uchida, M., Uglov, T., Unno, Y., Uno, S., Urquijo, P., Usov, Y., Varvell, K. E., Wang, E., Wang, M. -Z., Watanuki, S., Wiechczynski, J., Xu, X., Yabsley, B. D., Yan, W., Yang, S. B., Yin, J. H., Yuan, L., Zhang, Z. P., Zhilich, V., Zhukova, V.
We search for the baryon and lepton number violating charm decays, $D \rightarrow p\ell$, where $D$ is either a $D^0$ or a $\overline{D}^0$ and $\ell$ is a muon or an electron, using a data sample of $921\,\mathrm{fb}^{-1}$ collected by the Belle det
Externí odkaz:
http://arxiv.org/abs/2310.07412
Autor:
Will HG Cheng, Weinan Dong, Emily TY Tse, Carlos KH Wong, Weng Y Chin, Laura E Bedford, Daniel YT Fong, Welchie WK Ko, David VK Chao, Kathryn CB Tan, Cindy LK Lam
Publikováno v:
Journal of Diabetes Investigation, Vol 15, Iss 9, Pp 1317-1325 (2024)
ABSTRACT Aims/Introduction Two Hong Kong Chinese non‐laboratory‐based prediabetes/diabetes mellitus (pre‐DM/DM) risk models were developed using logistic regression (LR) and machine learning, respectively. We aimed to evaluate the models' valid
Externí odkaz:
https://doaj.org/article/8827314f1b724640b05af19e1d064415
Autor:
Daniel Garcia-Ovejero, Evelyn Beyerer, Orpheus Mach, Iris Leister, Martin Strowitzki, Christof Wutte, Doris Maier, John LK Kramer, Ludwig Aigner, Angel Arevalo-Martin, Lukas Grassner
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-17 (2024)
Abstract Background The discovery of new prognostic biomarkers following spinal cord injury (SCI) is a rapidly growing field that could help uncover the underlying pathological mechanisms of SCI and aid in the development of new therapies. To date, t
Externí odkaz:
https://doaj.org/article/774e8d415fbb4a3a8581b08cc9251e7a
Publikováno v:
Clinical Ophthalmology, Vol Volume 18, Pp 1901-1908 (2024)
Kaustav Banerjee,1 Subhasish Pramanik,2 Lakshmi Kanta Mondal3 1Decision Sciences Area, Indian Institute of Management Lucknow, Uttar Pradesh, 226013, India; 2Department of Endocrinology & Metabolism, Institute of Post Graduate Medical Education & Res
Externí odkaz:
https://doaj.org/article/0c22238c797746669b773862049682af
Autor:
Tung, Hsiao-Yu, Ding, Mingyu, Chen, Zhenfang, Bear, Daniel, Gan, Chuang, Tenenbaum, Joshua B., Yamins, Daniel LK, Fan, Judith E, Smith, Kevin A.
General physical scene understanding requires more than simply localizing and recognizing objects -- it requires knowledge that objects can have different latent properties (e.g., mass or elasticity), and that those properties affect the outcome of p
Externí odkaz:
http://arxiv.org/abs/2306.15668
Autor:
Xue, Haotian, Torralba, Antonio, Tenenbaum, Joshua B., Yamins, Daniel LK, Li, Yunzhu, Tung, Hsiao-Yu
Given a visual scene, humans have strong intuitions about how a scene can evolve over time under given actions. The intuition, often termed visual intuitive physics, is a critical ability that allows us to make effective plans to manipulate the scene
Externí odkaz:
http://arxiv.org/abs/2304.11470
While machine-learned interatomic potentials have become a mainstay for modeling materials, designing training sets that lead to robust potentials is challenging. Automated methods, such as active learning and on-the-fly learning, construct reliable
Externí odkaz:
http://arxiv.org/abs/2304.01314
Publikováno v:
Journal of Multidisciplinary Healthcare, Vol Volume 17, Pp 2879-2890 (2024)
Lena-Karin Gustafsson,1 Els-Marie Anbacken,2 Gunnel Östlund,2 Anna Bondesson,1 Tina Pettersson,1 Viktoria Zander3 1Division of Caring Science, School of Health, Care and Social Welfare, Mälardalens University, Eskilstuna, Sweden; 2Division of Socia
Externí odkaz:
https://doaj.org/article/fa054acbfac44b008e37932af75fc7be
Publikováno v:
JPRAS Open, Vol 40, Iss , Pp 215-221 (2024)
Aim: We present a case of Ecthyma gangrenosum (EG) affecting left thigh in a child with acute lymphoblastic leukaemia (ALL) with an aim to raise awareness about this condition. Case presentation: A 7-year-old female child who presented with lethargy,
Externí odkaz:
https://doaj.org/article/2786987815f24866a47feef9b80dfa5b