Zobrazeno 1 - 10
of 37 584
pro vyhledávání: '"A, Popp"'
Autor:
Gadhikar, Advait, Majumdar, Souptik Kumar, Popp, Niclas, Saranrittichai, Piyapat, Rapp, Martin, Schott, Lukas
Advancements in deep learning are driven by training models with increasingly larger numbers of parameters, which in turn heightens the computational demands. To address this issue, Mixture-of-Depths (MoD) models have been proposed to dynamically ass
Externí odkaz:
http://arxiv.org/abs/2412.20875
Autor:
Popp, Bruce D.
J. Willard Gibbs published a book in 1902 on statistical mechanics that quickly received significant attention from his contemporaries because of the reputation that he had secured with his prior work on thermodynamics. People reading Gibbs's book we
Externí odkaz:
http://arxiv.org/abs/2412.11425
Dense prediction tasks such as object detection and segmentation require high-quality labels at pixel level, which are costly to obtain. Recent advances in foundation models have enabled the generation of autolabels, which we find to be competitive b
Externí odkaz:
http://arxiv.org/abs/2412.10032
This paper explores the application of physics-informed neural networks (PINNs) to tackle forward problems in 3D contact mechanics, focusing on small deformation elasticity. We utilize a mixed-variable formulation, enhanced with output transformation
Externí odkaz:
http://arxiv.org/abs/2412.09022
Autor:
Leckenby, G., Sidhu, R. S., Chen, R. J., Mancino, R., Szányi, B., Bai, M., Battino, U., Blaum, K., Brandau, C., Cristallo, S., Dickel, T., Dillmann, I., Dmytriiev, D., Faestermann, T., Forstner, O., Franczak, B., Geissel, H., Gernhäuser, R., Glorius, J., Griffin, C., Gumberidze, A., Haettner, E., Hillenbrand, P. -M., Karakas, A., Kaur, T., Korten, W., Kozhuharov, C., Kuzminchuk, N., Langanke, K., Litvinov, S., Litvinov, Y. A., Lugaro, M., Martínez-Pinedo, G., Menz, E., Meyer, B., Morgenroth, T., Neff, T., Nociforo, C., Petridis, N., Pignatari, M., Popp, U., Purushothaman, S., Reifarth, R., Sanjari, S., Scheidenberger, C., Spillmann, U., Steck, M., Stöhlker, T., Tanaka, Y. K., Trassinelli, M., Trotsenko, S., Varga, L., Vescovi, D., Wang, M., Weick, H., López, A. Yagüe, Yamaguchi, T., Zhang, Y., Zhao, J.
Radioactive nuclei with lifetimes on the order of millions of years can reveal the formation history of the Sun and active nucleosynthesis occurring at the time and place of its birth. Among such nuclei whose decay signatures are found in the oldest
Externí odkaz:
http://arxiv.org/abs/2411.08856
Autor:
Li, Zexu, Prabhu, Suraj P., Popp, Zachary T., Jain, Shubhi S., Balakundi, Vijetha, Ang, Ting Fang Alvin, Au, Rhoda, Chen, Jinying
Biomedical research requires large, diverse samples to produce unbiased results. Automated methods for matching variables across datasets can accelerate this process. Research in this area has been limited, primarily focusing on lexical matching and
Externí odkaz:
http://arxiv.org/abs/2411.02730
The combined use of data from different sources can be critical in emergencies, where accurate models are needed to make real-time decisions, but high-fidelity representations and detailed information are simply unavailable. This study presents a dat
Externí odkaz:
http://arxiv.org/abs/2410.10346
Contaminant Dispersion Simulation in a Digital Twin Framework for Critical Infrastructure Protection
Autor:
von Danwitz, Max, Bonari, Jacopo, Franz, Philip, Kühn, Lisa, Mattuschka, Marco, Popp, Alexander
A digital twin framework for rapid predictions of atmospheric contaminant dispersion is developed to support informed decision making in emergency situations. In an offline preparation phase, the geometry of a built environment is discretized with a
Externí odkaz:
http://arxiv.org/abs/2409.01253
Labor market tightness tremendously increased in Germany between 2012 and 2022. We analyze the effect of tightness on wages by combining social security data with unusually rich information on vacancies and job seekers. Instrumental variable regressi
Externí odkaz:
http://arxiv.org/abs/2408.04508
Entanglement distillation, the process of converting weakly entangled states into maximally entangled ones using Local Operations and Classical Communication (LOCC), is pivotal for robust entanglement-assisted quantum information processing in error-
Externí odkaz:
http://arxiv.org/abs/2408.02383