Zobrazeno 1 - 10
of 19 500
pro vyhledávání: '"Jason, K."'
Autor:
ALLEN, JASON K.1
Publikováno v:
Eikon: A Journal for Biblical Anthropology. Spring2020, Vol. 2 Issue 1, p102-107. 6p.
Autor:
Cho, Jacqui1 (AUTHOR) jacqui.cho@swisspeace.ch
Publikováno v:
International Peacekeeping (13533312). Apr2024, Vol. 31 Issue 2, p278-281. 4p.
The rapid advancement of embedded multicore and many-core systems has revolutionized computing, enabling the development of high-performance, energy-efficient solutions for a wide range of applications. As models scale up in size, data movement is in
Externí odkaz:
http://arxiv.org/abs/2410.09650
Autor:
Du, Dongxue, Zhang, Cheyu, Wei, Jingrui, Teng, Yujia, Genser, Konrad, Voyles, Paul M., Rabe, Karin M., Kawasaki, Jason K.
Hexagonal $ABC$ intermetallics are predicted to have tunable ferroelectric, topological, and magnetic properties as a function of the polar buckling of $BC$ atomic planes. We report the impact of isovalent lanthanide substitution on the buckling, str
Externí odkaz:
http://arxiv.org/abs/2408.08290
Autor:
Dinkel, Holly M., Cornelius, Jason K.
The UN Office of Outer Space Affairs identifies synergy of space development activities and international cooperation through data and infrastructure sharing in their Sustainable Development Goal 17 (SDG17). Current multilateral space exploration par
Externí odkaz:
http://arxiv.org/abs/2408.04730
Autor:
Zhu, Rui-Jie, Zhang, Yu, Sifferman, Ethan, Sheaves, Tyler, Wang, Yiqiao, Richmond, Dustin, Zhou, Peng, Eshraghian, Jason K.
Matrix multiplication (MatMul) typically dominates the overall computational cost of large language models (LLMs). This cost only grows as LLMs scale to larger embedding dimensions and context lengths. In this work, we show that MatMul operations can
Externí odkaz:
http://arxiv.org/abs/2406.02528
Autonomous driving demands an integrated approach that encompasses perception, prediction, and planning, all while operating under strict energy constraints to enhance scalability and environmental sustainability. We present Spiking Autonomous Drivin
Externí odkaz:
http://arxiv.org/abs/2405.19687
Recent advancements in neuroscience research have propelled the development of Spiking Neural Networks (SNNs), which not only have the potential to further advance neuroscience research but also serve as an energy-efficient alternative to Artificial
Externí odkaz:
http://arxiv.org/abs/2405.13672
Weight quantization is used to deploy high-performance deep learning models on resource-limited hardware, enabling the use of low-precision integers for storage and computation. Spiking neural networks (SNNs) share the goal of enhancing efficiency, b
Externí odkaz:
http://arxiv.org/abs/2404.19668