On the Possibility of Small Networks for Physics-Informed Learning
Introduction in the period of 2017-2019, physics-informed neural networks (PINNs) have been a very popular area of research in the...
networks
Neural Networks Learn Entanglement Witnesses With Over 99% Accuracy For Quantum States
Detecting and characterizing entanglement remains a central challenge in quantum physics, and researchers are now exploring machine learning techniques to...
Educational attainment in sociocentric networks associates with cardiac biomarkers in Korean elders
Study design and participantsWe used a part of the prospective cohort data obtained from the Korean Social Life, Health and...
A multimodal deep reinforcement learning approach for IoT-driven adaptive scheduling and robustness optimization in global logistics networks
Multimodal data fusion frameworkEffective decision-making in global logistics networks requires comprehensive situational awareness derived from diverse data sources spanning physical...
Integrating graph and reinforcement learning for vaccination strategies in complex networks
Who coronavirus (covid-19) dashboard. (Accessed July 14, 2023). https://covid19.who.int/.Kang, Q. et al. Machine learning-aided causal inference framework for environmental data...
