Zobrazeno 1 - 10
of 11 308
pro vyhledávání: '"Heumann"'
Autor:
Negash S, Horn J, Heumann E, Stock C, Zeeb H, Pischke CR, Matos Fialho PM, Helmer SM, Niephaus Y, Mikolajczyk R
Publikováno v:
Psychology Research and Behavior Management, Vol Volume 17, Pp 2271-2285 (2024)
Sarah Negash,1 Johannes Horn,1 Eileen Heumann,2 Christiane Stock,2 Hajo Zeeb,3,4 Claudia R Pischke,5 Paula M Matos Fialho,5 Stefanie M Helmer,6 Yasemin Niephaus,7 Rafael Mikolajczyk1 1Institute for Medical Epidemiology, Biometrics and Informatics, In
Externí odkaz:
https://doaj.org/article/0b400ae0aec143428a6235352d1ff1c3
Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 213-216 (2022)
Blood sampling typically involves puncturing a superficial vein with a needle and then creating a vacuum (e. g., with a syringe) to transfer the blood from the venous system to the collection container. In some cases, the venous walls collapse due to
Externí odkaz:
https://doaj.org/article/2de47fff2ec64e6da1176b34bab8193a
Introduction Lifetime risks quantify health risks from radiation exposure and play an important role in radiation detriment and radon dose conversion. This study considers the lifetime risk of dying from lung cancer related to occupational radon expo
Externí odkaz:
http://arxiv.org/abs/2412.06054
Autor:
Arias, Esteban Garces, Blocher, Hannah, Rodemann, Julian, Li, Meimingwei, Heumann, Christian, Aßenmacher, Matthias
Open-ended text generation has become a prominent task in natural language processing due to the rise of powerful (large) language models. However, evaluating the quality of these models and the employed decoding strategies remains challenging becaus
Externí odkaz:
http://arxiv.org/abs/2410.18653
Autor:
Raymond, Alexander W., Doeleman, Sheperd S., Asada, Keiichi, Blackburn, Lindy, Bower, Geoffrey C., Bremer, Michael, Broguiere, Dominique, Chen, Ming-Tang, Crew, Geoffrey B., Dornbusch, Sven, Fish, Vincent L., García, Roberto, Gentaz, Olivier, Goddi, Ciriaco, Han, Chih-Chiang, Hecht, Michael H., Huang, Yau-De, Janssen, Michael, Keating, Garrett K., Koay, Jun Yi, Krichbaum, Thomas P., Lo, Wen-Ping, Matsushita, Satoki, Matthews, Lynn D., Moran, James M., Norton, Timothy J., Patel, Nimesh, Pesce, Dominic W., Ramakrishnan, Venkatessh, Rottmann, Helge, Roy, Alan L., Sánchez, Salvador, Tilanus, Remo P. J., Titus, Michael, Torne, Pablo, Wagner, Jan, Weintroub, Jonathan, Wielgus, Maciek, Young, André, Akiyama, Kazunori, Albentosa-Ruíz, Ezequiel, Alberdi, Antxon, Alef, Walter, Algaba, Juan Carlos, Anantua, Richard, Azulay, Rebecca, Bach, Uwe, Baczko, Anne-Kathrin, Ball, David, Baloković, Mislav, Bandyopadhyay, Bidisha, Barrett, John, Bauböck, Michi, Benson, Bradford A., Bintley, Dan, Blundell, Raymond, Bouman, Katherine L., Boyce, Hope, Brissenden, Roger, Britzen, Silke, Broderick, Avery E., Bronzwaer, Thomas, Bustamante, Sandra, Carlstrom, John E., Chael, Andrew, Chan, Chi-kwan, Chang, Dominic O., Chatterjee, Koushik, Chatterjee, Shami, Chen, Yongjun, Cheng, Xiaopeng, Cho, Ilje, Christian, Pierre, Conroy, Nicholas S., Conway, John E., Crawford, Thomas M., Cruz-Osorio, Alejandro, Cui, Yuzhu, Dahale, Rohan, Davelaar, Jordy, De Laurentis, Mariafelicia, Deane, Roger, Dempsey, Jessica, Desvignes, Gregory, Dexter, Jason, Dhruv, Vedant, Dihingia, Indu K., Dzib, Sergio A., Eatough, Ralph P., Emami, Razieh, Falcke, Heino, Farah, Joseph, Fomalont, Edward, Fontana, Anne-Laure, Ford, H. Alyson, Foschi, Marianna, Fraga-Encinas, Raquel, Freeman, William T., Friberg, Per, Fromm, Christian M., Fuentes, Antonio, Galison, Peter, Gammie, Charles F., Georgiev, Boris, Gold, Roman, Gómez-Ruiz, Arturo I., Gómez, José L., Gu, Minfeng, Gurwell, Mark, Hada, Kazuhiro, Haggard, Daryl, Hesper, Ronald, Heumann, Dirk, Ho, Luis C., Ho, Paul, Honma, Mareki, Huang, Chih-Wei L., Huang, Lei, Hughes, David H., Ikeda, Shiro, Impellizzeri, C. M. Violette, Inoue, Makoto, Issaoun, Sara, James, David J., Jannuzi, Buell T., Jeter, Britton, Jiang, Wu, Jiménez-Rosales, Alejandra, Johnson, Michael D., Jorstad, Svetlana, Jones, Adam C., Joshi, Abhishek V., Jung, Taehyun, Karuppusamy, Ramesh, Kawashima, Tomohisa, Kettenis, Mark, Kim, Dong-Jin, Kim, Jae-Young, Kim, Jongsoo, Kim, Junhan, Kino, Motoki, Kocherlakota, Prashant, Kofuji, Yutaro, Koch, Patrick M., Koyama, Shoko, Kramer, Carsten, Kramer, Joana A., Kramer, Michael, Kubo, Derek, Kuo, Cheng-Yu, La Bella, Noemi, Lee, Sang-Sung, Levis, Aviad, Li, Zhiyuan, Lico, Rocco, Lindahl, Greg, Lindqvist, Michael, Lisakov, Mikhail, Liu, Jun, Liu, Kuo, Liuzzo, Elisabetta, Lobanov, Andrei P., Loinard, Laurent, Lonsdale, Colin J., Lowitz, Amy E., Lu, Ru-Sen, MacDonald, Nicholas R., Mahieu, Sylvain, Maier, Doris, Mao, Jirong, Marchili, Nicola, Markoff, Sera, Marrone, Daniel P., Marscher, Alan P., Martí-Vidal, Iván, Medeiros, Lia, Menten, Karl M., Mizuno, Izumi, Mizuno, Yosuke, Montgomery, Joshua, Moriyama, Kotaro, Moscibrodzka, Monika, Mulaudzi, Wanga, Müller, Cornelia, Müller, Hendrik, Mus, Alejandro, Musoke, Gibwa, Myserlis, Ioannis, Nagai, Hiroshi, Nagar, Neil M., Nakamura, Masanori, Narayanan, Gopal, Natarajan, Iniyan, Nathanail, Antonios, Fuentes, Santiago Navarro, Neilsen, Joey, Ni, Chunchong, Nowak, Michael A., Oh, Junghwan, Okino, Hiroki, Sánchez, Héctor Raúl Olivares, Oyama, Tomoaki, Özel, Feryal, Palumbo, Daniel C. M., Paraschos, Georgios Filippos, Park, Jongho, Parsons, Harriet, Pen, Ue-Li, Piétu, Vincent, PopStefanija, Aleksandar, Porth, Oliver, Prather, Ben, Principe, Giacomo, Psaltis, Dimitrios, Pu, Hung-Yi, Raffin, Philippe A., Rao, Ramprasad, Rawlings, Mark G., Ricarte, Angelo, Ripperda, Bart, Roelofs, Freek, Romero-Cañizales, Cristina, Ros, Eduardo, Roshanineshat, Arash, Ruiz, Ignacio, Ruszczyk, Chet, Rygl, Kazi L. J., Sánchez-Argüelles, David, Sánchez-Portal, Miguel, Sasada, Mahito, Satapathy, Kaushik, Savolainen, Tuomas, Schloerb, F. Peter, Schonfeld, Jonathan, Schuster, Karl-Friedrich, Shao, Lijing, Shen, Zhiqiang, Small, Des, Sohn, Bong Won, SooHoo, Jason, Salas, León David Sosapanta, Souccar, Kamal, Srinivasan, Ranjani, Stanway, Joshua S., Sun, He, Tazaki, Fumie, Tetarenko, Alexandra J., Tiede, Paul, Toma, Kenji, Toscano, Teresa, Traianou, Efthalia, Trent, Tyler, Trippe, Sascha, Turk, Matthew, van Bemmel, Ilse, van Langevelde, Huib Jan, van Rossum, Daniel R., Vos, Jesse, Ward-Thompson, Derek, Wardle, John, Washington, Jasmin E., Wharton, Robert, Wiik, Kaj, Witzel, Gunther, Wondrak, Michael F., Wong, George N., Wu, Qingwen, Yadlapalli, Nitika, Yamaguchi, Paul, Yfantis, Aristomenis, Yoon, Doosoo, Younsi, Ziri, Yu, Wei, Yuan, Feng, Yuan, Ye-Fei, Zensus, J. Anton, Zhang, Shuo, Zhao, Guang-Yao, Zhao, Shan-Shan
Publikováno v:
The Astronomical Journal, Volume 168, Issue 3, id.130, 19 pp. 2024
The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-freque
Externí odkaz:
http://arxiv.org/abs/2410.07453
Decoding strategies for generative large language models (LLMs) are a critical but often underexplored aspect of text generation tasks. Guided by specific hyperparameters, these strategies aim to transform the raw probability distributions produced b
Externí odkaz:
http://arxiv.org/abs/2410.06097
In recent years, large language models (LLMs) have emerged as powerful tools with potential applications in various fields, including software engineering. Within the scope of this research, we evaluate five different state-of-the-art LLMs - Bard, Bi
Externí odkaz:
http://arxiv.org/abs/2409.04164
Autor:
Arias, Esteban Garces, Rodemann, Julian, Li, Meimingwei, Heumann, Christian, Aßenmacher, Matthias
Decoding from the output distributions of large language models to produce high-quality text is a complex challenge in language modeling. Various approaches, such as beam search, sampling with temperature, $k-$sampling, nucleus $p-$sampling, typical
Externí odkaz:
http://arxiv.org/abs/2407.18698
Autor:
Obster, Fabian, Heumann, Christian
This paper introduces the sgboost package in R, which implements sparse-group boosting for modeling high-dimensional data with natural groupings in covariates. Sparse-group boosting offers a flexible approach for both group and individual variable se
Externí odkaz:
http://arxiv.org/abs/2405.21037
Autor:
Heumann, Joakim
Continental ice sheet simulations are commonly based on either the Full Stokes (FS) model, or its simplification, the Shallow Ice Approximation (SIA) model. This thesis examines a machine learning error estimation approach for assessing the accuracy
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-349257