[HTML][HTML] Federated learning for 6G: Applications, challenges, and opportunities
Standard machine-learning approaches involve the centralization of training data in a data
center, where centralized machine-learning algorithms can be applied for data analysis and …
center, where centralized machine-learning algorithms can be applied for data analysis and …
A high-bias, low-variance introduction to machine learning for physicists
Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …
research and application. The purpose of this review is to provide an introduction to the core …
Machine learning–enabled high-entropy alloy discovery
High-entropy alloys are solid solutions of multiple principal elements that are capable of
reaching composition and property regimes inaccessible for dilute materials. Discovering …
reaching composition and property regimes inaccessible for dilute materials. Discovering …
Learning high-speed flight in the wild
Quadrotors are agile. Unlike most other machines, they can traverse extremely complex
environments at high speeds. To date, only expert human pilots have been able to fully …
environments at high speeds. To date, only expert human pilots have been able to fully …
Gflownet foundations
Generative Flow Networks (GFlowNets) have been introduced as a method to sample a
diverse set of candidates in an active learning context, with a training objective that makes …
diverse set of candidates in an active learning context, with a training objective that makes …
A survey of application research based on blockchain smart contract
SY Lin, L Zhang, J Li, L Ji, Y Sun - Wireless Networks, 2022 - Springer
Nowadays, blockchain technology and industry has developed rapidly all over the world,
which is inseparable from continuous innovation and improvement on smart contract …
which is inseparable from continuous innovation and improvement on smart contract …
[HTML][HTML] Two-stage aging trajectory prediction of LFP lithium-ion battery based on transfer learning with the cycle life prediction
With the wide application of the LFP lithium-ion batteries, more attention is paid to the battery
life and future aging behaviors as the safety and performance of the battery are guaranteed …
life and future aging behaviors as the safety and performance of the battery are guaranteed …
[HTML][HTML] An explainable AI (XAI) model for landslide susceptibility modeling
Landslides are among the most devastating natural hazards, severely impacting human
lives and damaging property and infrastructure. Landslide susceptibility maps, which help to …
lives and damaging property and infrastructure. Landslide susceptibility maps, which help to …
Artificial neural networks-based machine learning for wireless networks: A tutorial
In order to effectively provide ultra reliable low latency communications and pervasive
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
Assessments of landslide disasters are becoming increasingly urgent. The aim of this study
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …
is to investigate a convolutional neural network (CNN) framework for landslide susceptibility …