Zobrazeno 1 - 10
of 5 758
pro vyhledávání: '"Spanring"'
Autor:
Turk Spela, Plahuta Irena, Magdalenic Tomislav, Spanring Tajda, Laufer Kevin, Mavc Zan, Potrc Stojan, Ivanecz Arpad
Publikováno v:
Radiology and Oncology, Vol 57, Iss 2, Pp 270-278 (2023)
Two-stage hepatectomy (TSH) has been proposed for patients with bilateral liver tumours who have a high risk of posthepatectomy liver failure after one-stage hepatectomy (OSH). This study aimed to determine the outcomes of TSH for extensive bilateral
Externí odkaz:
https://doaj.org/article/88881ff75d704e4d88131043bb67b8f9
Autor:
Beck, Maximilian, Pöppel, Korbinian, Spanring, Markus, Auer, Andreas, Prudnikova, Oleksandra, Kopp, Michael, Klambauer, Günter, Brandstetter, Johannes, Hochreiter, Sepp
In the 1990s, the constant error carousel and gating were introduced as the central ideas of the Long Short-Term Memory (LSTM). Since then, LSTMs have stood the test of time and contributed to numerous deep learning success stories, in particular the
Externí odkaz:
http://arxiv.org/abs/2405.04517
Autor:
Neun, Moritz, Eichenberger, Christian, Martin, Henry, Spanring, Markus, Siripurapu, Rahul, Springer, Daniel, Deng, Leyan, Wu, Chenwang, Lian, Defu, Zhou, Min, Lumiste, Martin, Ilie, Andrei, Wu, Xinhua, Lyu, Cheng, Lu, Qing-Long, Mahajan, Vishal, Lu, Yichao, Li, Jiezhang, Li, Junjun, Gong, Yue-Jiao, Grötschla, Florian, Mathys, Joël, Wei, Ye, Haitao, He, Fang, Hui, Malm, Kevin, Tang, Fei, Kopp, Michael, Kreil, David, Hochreiter, Sepp
The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem in a data-driven way, advancing the latest methods in machine learning
Externí odkaz:
http://arxiv.org/abs/2303.07758
A growing number of Machine Learning Frameworks recently made Deep Learning accessible to a wider audience of engineers, scientists, and practitioners, by allowing straightforward use of complex neural network architectures and algorithms. However, s
Externí odkaz:
http://arxiv.org/abs/2211.04908
Autor:
Eichenberger, Christian, Neun, Moritz, Martin, Henry, Herruzo, Pedro, Spanring, Markus, Lu, Yichao, Choi, Sungbin, Konyakhin, Vsevolod, Lukashina, Nina, Shpilman, Aleksei, Wiedemann, Nina, Raubal, Martin, Wang, Bo, Vu, Hai L., Mohajerpoor, Reza, Cai, Chen, Kim, Inhi, Hermes, Luca, Melnik, Andrew, Velioglu, Riza, Vieth, Markus, Schilling, Malte, Bojesomo, Alabi, Marzouqi, Hasan Al, Liatsis, Panos, Santokhi, Jay, Hillier, Dylan, Yang, Yiming, Sarwar, Joned, Jordan, Anna, Hewage, Emil, Jonietz, David, Tang, Fei, Gruca, Aleksandra, Kopp, Michael, Kreil, David, Hochreiter, Sepp
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggregated GPS probe data in time and space bins. We thus reinterpreted the c
Externí odkaz:
http://arxiv.org/abs/2203.17070
Today's blockchain landscape is severely fragmented as more and more heterogeneous blockchain platforms have been developed in recent years. These blockchain platforms are not able to interact with each other or with the outside world since only litt
Externí odkaz:
http://arxiv.org/abs/2111.10091
Today, several solutions for cross-blockchain asset transfers exist. However, these solutions are either tailored to specific assets or neglect finality guarantees that prevent assets from getting lost in transit. In this paper, we present a cross-bl
Externí odkaz:
http://arxiv.org/abs/2004.10488
Current blockchain technologies provide very limited means of interoperability. In particular, solutions enabling blockchains to verify the existence of data on other blockchains are either very costly or are not fully decentralized. To overcome thes
Externí odkaz:
http://arxiv.org/abs/2002.12837