Zobrazeno 1 - 10
of 219 646
pro vyhledávání: '"A, Osman"'
Autor:
Križan, Christian, Biznárová, Janka, Chen, Liangyu, Hogedal, Emil, Osman, Amr, Warren, Christopher W., Kosen, Sandoko, Li, Hang-Xi, Abad, Tahereh, Aggarwal, Anuj, Caputo, Marco, Fernández-Pendás, Jorge, Gaikwad, Akshay, Grönberg, Leif, Nylander, Andreas, Rehammar, Robert, Rommel, Marcus, Yuzephovich, Olga I., Kockum, Anton Frisk, Govenius, Joonas, Tancredi, Giovanna, Bylander, Jonas
It is advantageous for any quantum processor to support different classes of two-qubit quantum logic gates when compiling quantum circuits, a property that is typically not seen with existing platforms. In particular, access to a gate set that includ
Externí odkaz:
http://arxiv.org/abs/2412.15022
Autor:
Byggmästar, Jesper, Sobieraj, Damian, Wróbel, Jan S., Schreiber, Daniel K., El-Atwani, Osman, Martinez, Enrique, Nguyen-Manh, Duc
Tungsten-based low-activation high-entropy alloys are possible candidates for next-generation fusion reactors due to their exceptional tolerance to irradiation, thermal loads, and stress. We develop an accurate and efficient machine-learned interatom
Externí odkaz:
http://arxiv.org/abs/2412.13750
Autor:
Nahavandian, Mohammadhossein, Aydogan, Eda, Byggmästar, Jesper, Tunes, Matheus A., Martinez, Enrique, El-Atwani, Osman
High entropy alloys (HEAs) have captured much attention in recent years due to their conceivably improved radiation resistance compared to pure metals and traditional alloys. However, among HEAs, there are millions of design possibilities considering
Externí odkaz:
http://arxiv.org/abs/2412.13343
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