Zobrazeno 1 - 10
of 315 197
pro vyhledávání: '"A. JACOBS"'
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 23, Pp 3261-3284 (2023)
Probabilistic models to inform landslide early warning systems often rely on rainfall totals observed during past events with landslides. However, these models are generally developed for broad regions using large catalogs, with dozens, hundreds, or
Externí odkaz:
https://doaj.org/article/7e02cdb8770a4c0c864f9318a0f56865
Autor:
Li, Jialu, Li, Yuanzhen, Wadhwa, Neal, Pritch, Yael, Jacobs, David E., Rubinstein, Michael, Bansal, Mohit, Ruiz, Nataniel
We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired by James P. Carse's distinction between finite and infinite games, we l
Externí odkaz:
http://arxiv.org/abs/2410.18975
Autor:
Bombaerts, Gunter, Hannes, Tom, Adam, Martin, Aloisi, Alessandra, Anderson, Joel, Berger, Lawrence, Bettera, Stefano Davide, Campo, Enrico, Candiotto, Laura, Panizza, Silvia Caprioglio, Citton, Yves, DâAngelo, Diego, Dennis, Matthew, Depraz, Nathalie, Doran, Peter, Drechsler, Wolfgang, Duane, Bill, Edelglass, William, Eisenberger, Iris, McGuire, Beverley Foulks, Fredriksson, Antony, Gill, Karamjit S., Hershock, Peter D., Hongladarom, Soraj, Jacobs, Beth, Karsai, Gábor, Lennerfors, Thomas, Lim, Jeanne, Lin, Chien-Te, Losoncz, Mark, Loy, David, Marin, Lavinia, Marosán, Bence Péter, Mascarello, Chiara, McMahan, David, Park, Jin Y., Petek, Nina, Puzio, Anna, Schaubroek, Katrien, Schlieter, Jens, Schroeder, Brian, Shakya, Shobhit, Shi, Juewei, Solomonova, Elizaveta, Tormen, Francesco, Uttam, Jitendra, Van Vugt, Marieke, Vörös, Sebastjan, Wehrle, Maren, Wellner, Galit, Wirth, Jason M., Witkowski, Olaf, Wongkitrungrueng, Apiradee, Wright, Dale S., Zheng, Yutong
As the signatories of this manifesto, we denounce the attention economy as inhumane and a threat to our sociopolitical and ecological well-being. We endorse policymakers' efforts to address the negative consequences of the attention economy's technol
Externí odkaz:
http://arxiv.org/abs/2410.17421
Autor:
Belle Collaboration, Boschetti, A., Mussa, R., Tamponi, U., Adachi, I., Aihara, H., Asner, D. M., Aushev, T., Ayad, R., Banerjee, Sw., Belous, K., Bennett, J., Bessner, M., Biswas, D., Bobrov, A., Bodrov, D., Bozek, A., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Chang, M. -C., Cheon, B. G., Chilikin, K., Cho, K., Choi, S. -K., Choi, Y., Choudhury, S., De Nardo, G., De Pietro, G., Dhamija, R., Di Capua, F., Doležal, Z., Dong, T. V., Ecker, P., Epifanov, D., Ferlewicz, D., Fulsom, B. G., Garg, R., Gaur, V., Garmash, A., Giri, A., Goldenzweig, P., Graziani, E., Gu, T., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hara, T., Hayasaka, K., Hayashii, H., Hazra, S., Hou, W. -S., Hsu, C. -L., Inami, K., Ipsita, N., Itoh, R., Iwasaki, M., Jacobs, W. W., Jin, Y., Kawasaki, T., Kiesling, C., Kim, C. H., Kim, D. Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Korpar, S., Kovalenko, E., Križan, P., Krokovny, P., Kumar, R., Kumara, K., Kwon, Y. -J., Lam, T., Levit, D., Li, L. K., Li, Y. B., Gioi, L. Li, Liventsev, D., Ma, Y., Masuda, M., Matsuda, T., Matvienko, D., Meier, F., Merola, M., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Nakao, M., Natkaniec, Z., Natochii, A., Nayak, L., Nayak, M., Nishida, S., Ogawa, S., Ono, H., Pakhlova, G., Park, J., Park, S. -H., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Rout, N., Russo, G., Sandilya, S., Santelj, L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Shan, W., Shen, C. P., Shiu, J. -G., Sokolov, A., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tanida, K., Tenchini, F., Tiwary, R., Uchida, M., Unno, Y., Uno, S., Vinokurova, A., Wang, E., Wang, M. -Z., Wang, X. L., Won, E., Yabsley, B. D., Yelton, J., Yin, J. H., Yook, Y., Yuan, L.
In the bottomonium sector, the hindered magnetic dipole (M1) transitions between P-wave states $h_b(2P) \rightarrow \chi_{bJ}(1P) \gamma$, $J=0, \, 1, \, 2$, are expected to be severely suppressed according to the Relativized Quark Model, due to the
Externí odkaz:
http://arxiv.org/abs/2410.16181
Inverse Compton (IC) emission associated with the non-thermal component of the intracluster medium (ICM) has been a long sought phenomenon in cluster physics. Traditional spectral fitting often suffers from the degeneracy between the two-temperature
Externí odkaz:
http://arxiv.org/abs/2410.12943
In this work we compare the generative behavior at the next token prediction level in several language models by comparing them to human productions in the cloze task. We find that while large models trained for longer are typically better estimators
Externí odkaz:
http://arxiv.org/abs/2410.12057
Autor:
Un, Hio-Ieng, Iwanowski, Kamil, Orri, Jordi Ferrer, Jacobs, Ian E., Fukui, Naoya, Cornil, David, Beljonne, David, Simoncelli, Michele, Nishihara, Hiroshi, Sirringhaus, Henning
Thermoelectric materials, enabling direct waste-heat to electricity conversion, need to be highly electrically conducting while simultaneously thermally insulating. This is fundamentally challenging since electrical and thermal conduction are usually
Externí odkaz:
http://arxiv.org/abs/2410.11555
Autor:
Jacobs, Bob, Désert, Jean-Michel, Lewis, Nikole, Challener, Ryan C., Mayorga, L. C., de Beurs, Zoë, Parmentier, Vivien, Stevenson, Kevin B., de Wit, Julien, Barat, Saugata, Fortney, Jonathan, Kataria, Tiffany, Line, Michael
The extreme environments of transiting close-in exoplanets in highly-eccentric orbits are ideal for testing exo-climate physics. Spectroscopically resolved phase curves not only allow for the characterization of their thermal response to irradiation
Externí odkaz:
http://arxiv.org/abs/2410.11643
Probabilistic puzzles can be confusing, partly because they are formulated in natural languages - full of unclarities and ambiguities - and partly because there is no widely accepted and intuitive formal language to express them. We propose a simple
Externí odkaz:
http://arxiv.org/abs/2410.10643
In this work, we propose FlowMRI-Net, a novel deep learning-based framework for fast reconstruction of accelerated 4D flow magnetic resonance imaging (MRI) using physics-driven unrolled optimization and a complexvalued convolutional recurrent neural
Externí odkaz:
http://arxiv.org/abs/2410.08856