This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
Enhancing Mathematics Learning for Students with Intellectual and Developmental Disabilities in China: A Qualitative Study of Instructional Support. [PDF]
Yan T, Jin Y.
europepmc +1 more source
Physical literacy conceptions in teacher training: a longitudinal study. [PDF]
Hernaiz-Sánchez A +3 more
europepmc +1 more source
The influence of teacher care on middle school students' social-emotional competence: evidence from the China Education Panel Survey (2013-2014). [PDF]
Zhang Z, Li X, Juan G, Qi C.
europepmc +1 more source
Implementing martial arts education in Chinese schools: teachers' perspectives on the school martial arts program. [PDF]
Xue S, Ji H, Yang J, Zhao L, Su X.
europepmc +1 more source
Multimodal deep learning for sports teacher behavior analysis: design and evaluation of a personalized continuing education recommendation system. [PDF]
Chen Z.
europepmc +1 more source

