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pro vyhledávání: '"and Mohamed, S."'
Elastoviscoplastic (EVP) fluids, which exhibit both solid-like and liquid-like behavior depending on the applied stress, are critical in industrial processes involving complex geometries such as porous media and wavy channels. In this study, we inves
Externí odkaz:
http://arxiv.org/abs/2409.15935
Bit-level sparsity methods skip ineffectual zero-bit operations and are typically applicable within bit-serial deep learning accelerators. This type of sparsity at the bit-level is especially interesting because it is both orthogonal and compatible w
Externí odkaz:
http://arxiv.org/abs/2409.05227
Autor:
Chang, Chi-Chih, Lin, Wei-Cheng, Lin, Chien-Yu, Chen, Chong-Yan, Hu, Yu-Fang, Wang, Pei-Shuo, Huang, Ning-Chi, Ceze, Luis, Abdelfattah, Mohamed S., Wu, Kai-Chiang
Post-training KV-Cache compression methods typically either sample a subset of effectual tokens or quantize the data into lower numerical bit width. However, these methods cannot exploit redundancy in the hidden dimension of the KV tensors. This pape
Externí odkaz:
http://arxiv.org/abs/2407.21118
Autor:
Pellegrino, C., Modjaz, M., Takei, Y., Tsuna, D., Newsome, M., Pritchard, T., Baer-Way, R., Bostroem, K. A., Chandra, P., Charalampopoulos, P., Dong, Y., Farah, J., Howell, D. A., McCully, C., Mohamed, S., Gonzalez, E. Padilla, Terreran, G.
Type Ibn supernovae (SNe Ibn) are rare stellar explosions powered primarily by interaction between the SN ejecta and H-poor, He-rich material lost by their progenitor stars. Multi-wavelength observations, particularly in the X-rays, of SNe Ibn constr
Externí odkaz:
http://arxiv.org/abs/2407.18291
Autor:
Radwan, Ahmed, Shehata, Mohamed S.
Federated Domain Generalization (FedDG), aims to tackle the challenge of generalizing to unseen domains at test time while catering to the data privacy constraints that prevent centralized data storage from different domains originating at various cl
Externí odkaz:
http://arxiv.org/abs/2407.14792
Medical imaging tasks are very challenging due to the lack of publicly available labeled datasets. Hence, it is difficult to achieve high performance with existing deep-learning models as they require a massive labeled dataset to be trained effective
Externí odkaz:
http://arxiv.org/abs/2407.14784
Achieving domain generalization in medical imaging poses a significant challenge, primarily due to the limited availability of publicly labeled datasets in this domain. This limitation arises from concerns related to data privacy and the necessity fo
Externí odkaz:
http://arxiv.org/abs/2407.14719
FPGAs offer a flexible platform for accelerating deep neural network (DNN) inference, particularly for non-uniform workloads featuring fine-grained unstructured sparsity and mixed arithmetic precision. To leverage these redundancies, an emerging appr
Externí odkaz:
http://arxiv.org/abs/2407.06033
Autor:
Aboueisha, Mohamed S., Saad, A. S., Nouh, Mohamed I., Kamel, Tarek M., Beheary, M. M., Gadallah, Kamel A. K.
Publikováno v:
Physica Scripta, 99, 075052, 2024
In astrophysics, the gravitational stability of a self-gravitating polytropic fluid sphere is an intriguing subject, especially when trying to comprehend the genesis and development of celestial bodies like planets and stars. This stability is the sp
Externí odkaz:
http://arxiv.org/abs/2407.06238
Autor:
Eijnden, J. van den, Mohamed, S., Carotenuto, F., Motta, S., Saikia, P., Williams-Baldwin, D. R. A.
Massive stars that travel at supersonic speeds can create bow shocks as their stellar winds interact with the surrounding interstellar medium. These bow shocks - prominent sites for mechanical feedback of individual massive stars - are predominantly
Externí odkaz:
http://arxiv.org/abs/2407.00380