Zobrazeno 1 - 10
of 216 704
pro vyhledávání: '"A Osman"'
Autor:
Akar, Osman, Han, Yushan, Chen, Yizhou, Lan, Weixian, Gallagher, Benn, Fedkiw, Ronald, Teran, Joseph
We present learning-based implicit shape representations designed for real-time avatar collision queries arising in the simulation of clothing. Signed distance functions (SDFs) have been used for such queries for many years due to their computational
Externí odkaz:
http://arxiv.org/abs/2411.06719
Federated learning has recently gained popularity as a framework for distributed clients to collaboratively train a machine learning model using local data. While traditional federated learning relies on a central server for model aggregation, recent
Externí odkaz:
http://arxiv.org/abs/2410.18862
The High Temperature Reactor Code Package provides sophisticated modeling and simulation capabilities for high temperature gas cooled reactors like the HTR-200 Modul. However, HCP currently lacks integrated methods for uncertainty quantification and
Externí odkaz:
http://arxiv.org/abs/2411.03329
We introduce a dynamic spatiotemporal volatility model that extends traditional approaches by incorporating spatial, temporal, and spatiotemporal spillover effects, along with volatility-specific observed and latent factors. The model offers a more g
Externí odkaz:
http://arxiv.org/abs/2410.16526
We present a neural network-enhanced column generation (CG) approach for a parallel machine scheduling problem. The proposed approach utilizes an encoder-decoder attention model, namely the transformer and pointer architectures, to develop job sequen
Externí odkaz:
http://arxiv.org/abs/2410.15601
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems (Early Access) 2024
High-quality spatiotemporal traffic data is crucial for intelligent transportation systems (ITS) and their data-driven applications. Inevitably, the issue of missing data caused by various disturbances threatens the reliability of data acquisition. R
Externí odkaz:
http://arxiv.org/abs/2410.15248
Autor:
Minhas, Mishal Fatima, Putra, Rachmad Vidya Wicaksana, Awwad, Falah, Hasan, Osman, Shafique, Muhammad
To adapt to real-world dynamics, intelligent systems need to assimilate new knowledge without catastrophic forgetting, where learning new tasks leads to a degradation in performance on old tasks. To address this, continual learning concept is propose
Externí odkaz:
http://arxiv.org/abs/2410.09218
The Greenland Ice Sheet (GrIS) has emerged as a significant contributor to global sea level rise, primarily due to increased meltwater runoff. Supraglacial lakes, which form on the ice sheet surface during the summer months, can impact ice sheet dyna
Externí odkaz:
http://arxiv.org/abs/2410.05638
In an increasingly interconnected world, a key scientific challenge is to examine mechanisms that lead to the widespread propagation of contagions, such as misinformation and pathogens, and identify risk factors that can trigger large-scale outbreaks
Externí odkaz:
http://arxiv.org/abs/2409.17352
Autor:
Chen, Liangyu, Fors, Simon Pettersson, Yan, Zixian, Ali, Anaida, Abad, Tahereh, Osman, Amr, Moschandreou, Eleftherios, Lienhard, Benjamin, Kosen, Sandoko, Li, Hang-Xi, Shiri, Daryoush, Liu, Tong, Hill, Stefan, Amin, Abdullah-Al, Rehammar, Robert, Dahiya, Mamta, Nylander, Andreas, Rommel, Marcus, Roudsari, Anita Fadavi, Caputo, Marco, Leif, Grönberg, Govenius, Joonas, Dobsicek, Miroslav, Giannelli, Michele Faucci, Kockum, Anton Frisk, Bylander, Jonas, Tancredi, Giovanna
The realization of fault-tolerant quantum computing requires the execution of quantum error-correction (QEC) schemes, to mitigate the fragile nature of qubits. In this context, to ensure the success of QEC, a protocol capable of implementing both qub
Externí odkaz:
http://arxiv.org/abs/2409.16748