Application of artificial intelligence in predicting earthquakes: state-of-the-art and future challenges
Predicting the time, location and magnitude of an earthquake is a challenging job as an
earthquake does not show specific patterns resulting in inaccurate predictions. Techniques …
earthquake does not show specific patterns resulting in inaccurate predictions. Techniques …
Attention-based bi-directional long-short term memory network for earthquake prediction
An earthquake is a tremor felt on the surface of the earth created by the movement of the
major pieces of its outer shell. Till now, many attempts have been made to forecast …
major pieces of its outer shell. Till now, many attempts have been made to forecast …
Modeling Events and Interactions through Temporal Processes--A Survey
In real-world scenario, many phenomena produce a collection of events that occur in
continuous time. Point Processes provide a natural mathematical framework for modeling …
continuous time. Point Processes provide a natural mathematical framework for modeling …
Learning-motivation-boosted Explainable Temporal Point Process Model for Course Recommendation
W Zhang, X Zhou, X Zeng, S Zhu - IEEE Access, 2024 - ieeexplore.ieee.org
Course recommendation is vital for improving students' learning efficiency. In the learning
process, students' interests evolve, learning cycles and course scheduling are closely …
process, students' interests evolve, learning cycles and course scheduling are closely …
Information cascades prediction with graph attention
Z Chen, J Wei, S Liang, T Cai, X Liao - Frontiers in Physics, 2021 - frontiersin.org
The cascades prediction aims to predict the possible information diffusion path in the future
based on cascades of the social network. Recently, the existing researches based on deep …
based on cascades of the social network. Recently, the existing researches based on deep …
Wasserstein generative adversarial networks for modeling marked events
Marked temporal events are ubiquitous in several areas, where the events' times and marks
(types) are usually interrelated. Point processes and their non-functional variations using …
(types) are usually interrelated. Point processes and their non-functional variations using …
Artificial Cognition of Temporal Events Using Recurrent Point Process Networks
N Bala Sundara Ganapathy, M Deeptavarna - Computer Vision and …, 2022 - Springer
Data generated by real-world events are usually obtained by condensing events into
continuous signals at specific intervals, which are handled by mechanisms that make this …
continuous signals at specific intervals, which are handled by mechanisms that make this …
[图书][B] Intelligent Healthcare Process Discovery and Operational Coordination Using Discrete Event Simulation and Machine Learning
S Yildirim - 2021 - search.proquest.com
The healthcare system in the US is rapidly changing and reshaping to adopt continuously
evolving demand for improved operational efficiency and treatment effectiveness from …
evolving demand for improved operational efficiency and treatment effectiveness from …