Zobrazeno 1 - 10
of 81 157
pro vyhledávání: '"SABINE, P. A."'
Autor:
Mai, Yifan, Croom, Scott M., Wisnioski, Emily, Vaughan, Sam P., Varidel, Mathew R., Battisti, Andrew J., Mendel, J. Trevor, Mun, Marcie, Tsukui, Takafumi, Foster, Caroline, Harborne, Katherine E., Lagos, Claudia D. P., Wang, Di, Bellstedt, Sabine, Bland-Hawthorn, Joss, Colless, Matthew, D'Eugenio, Francesco, Grasha, Kathryn, Peng, Yingjie, Santucci, Giulia, Sweet, Sarah M., Thater, Sabine, Valenzuela, Lucas M., Ziegler, Bodo
We measure the ionised gas velocity dispersions of star-forming galaxies in the MAGPI survey ($z\sim0.3$) and compare them with galaxies in the SAMI ($z\sim0.05$) and KROSS ($z\sim1$) surveys to investigate how the ionised gas velocity dispersion evo
Externí odkaz:
http://arxiv.org/abs/2408.12224
We use a volume-complete sample of ~8,000 galaxies from the GAMA survey to characterise the impact of stellar population libraries (SPLs) and model configurations on the resulting inferred galaxy properties from Spectral Energy Distribution (SED) fit
Externí odkaz:
http://arxiv.org/abs/2410.17698
Autor:
Sfeir, Anthony, Petkova, Asya, Chaaya, Sabine, Chichova, Karina, Rossi, Marta, Vock, Anna, Mosut, Alessandro, Saravanaraj, Akshayanivasini Ramasamy, Sumini, Valentina, Nilsson, Tommy
As humans venture deeper into space, the need for a lunar settlement, housing the first group of settlers, grows steadily. By means of new technologies such as in situ resource utilisation (ISRU) as well as computational design, this goal can be impl
Externí odkaz:
http://arxiv.org/abs/2410.17114
Autor:
Carvalho, Matheus C., Naguleswaran, Bavithra, Barmby, Pauline, Gorski, Mark, Köenig, Sabine, Holwerda, Benne, Young, Jason E.
UGC 2885 (z = 0.01935) is one of the largest and most massive galaxies in the local Universe, yet its undisturbed spiral structure is unexpected for such an object and unpredicted in cosmological simulations. Understanding the detailed properties of
Externí odkaz:
http://arxiv.org/abs/2410.16467
Autor:
Ma, Yanan, Xiao, Chenghao, Yuan, Chenhan, van der Veer, Sabine N, Hassan, Lamiece, Lin, Chenghua, Nenadic, Goran
Topic modelling is a pivotal unsupervised machine learning technique for extracting valuable insights from large document collections. Existing neural topic modelling methods often encode contextual information of documents, while ignoring contextual
Externí odkaz:
http://arxiv.org/abs/2410.15136
The visual representation of a concept varies significantly depending on its meaning and the context where it occurs; this poses multiple challenges both for vision and multimodal models. Our study focuses on concreteness, a well-researched lexical-s
Externí odkaz:
http://arxiv.org/abs/2410.11657
The construction of coarse-grained descriptions of a system's kinetics is well established in biophysics. One prominent example is Markov state models in protein folding dynamics. In this paper, we develop a coarse-grained, discrete state model of a
Externí odkaz:
http://arxiv.org/abs/2410.09481
Autor:
Schäfer, Johannes, Combs, Aidan, Bagdon, Christopher, Li, Jiahui, Probol, Nadine, Greschner, Lynn, Papay, Sean, Resendiz, Yarik Menchaca, Velutharambath, Aswathy, Wührl, Amelie, Weber, Sabine, Klinger, Roman
Demographics and cultural background of annotators influence the labels they assign in text annotation -- for instance, an elderly woman might find it offensive to read a message addressed to a "bro", but a male teenager might find it appropriate. It
Externí odkaz:
http://arxiv.org/abs/2410.08820
Autor:
Rahmani, Saeed, Rieder, Sabine, de Gelder, Erwin, Sonntag, Marcel, Mallada, Jorge Lorente, Kalisvaart, Sytze, Hashemi, Vahid, Calvert, Simeon C.
The rapid development of automated vehicles (AVs) promises to revolutionize transportation by enhancing safety and efficiency. However, ensuring their reliability in diverse real-world conditions remains a significant challenge, particularly due to r
Externí odkaz:
http://arxiv.org/abs/2410.08491
Since neural networks can make wrong predictions even with high confidence, monitoring their behavior at runtime is important, especially in safety-critical domains like autonomous driving. In this paper, we combine ideas from previous monitoring app
Externí odkaz:
http://arxiv.org/abs/2410.06051