Epidemic spreading on spatial higher-order network
W Gu, Y Qiu, W Li, Z Zhang, X Liu, Y Song… - … Journal of Nonlinear …, 2024 - pubs.aip.org
Higher-order interactions exist widely in mobile populations and are extremely important in
spreading epidemics, such as influenza. However, research on high-order interaction …
spreading epidemics, such as influenza. However, research on high-order interaction …
[PDF][PDF] Hierarchical reinforcement learning on multi-channel hypergraph neural network for course recommendation
With the widespread popularity of massive open online courses, personalized course
recommendation has become increasingly important due to enhancing users' learning …
recommendation has become increasingly important due to enhancing users' learning …
MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity
Retrieval Augmented Generation (RAG) has proven to be highly effective in boosting the
generative performance of language model in knowledge-intensive tasks. However, existing …
generative performance of language model in knowledge-intensive tasks. However, existing …
[PDF][PDF] Hierarchical reinforcement learning for point of interest recommendation
With the increasing popularity of location-based services, accurately recommending points
of interest (POIs) has become a critical task. Although existing technologies are proficient in …
of interest (POIs) has become a critical task. Although existing technologies are proficient in …
[PDF][PDF] Decoupled invariant attention network for multivariate time-series forecasting
To achieve more accurate prediction results in Time Series Forecasting (TSF), it is essential
to distinguish between the valuable patterns (invariant patterns) of the spatial-temporal …
to distinguish between the valuable patterns (invariant patterns) of the spatial-temporal …
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
Urban traffic speed prediction aims to estimate the future traffic speed for improving urban
transportation services. Enormous efforts have been made to exploit Graph Neural Networks …
transportation services. Enormous efforts have been made to exploit Graph Neural Networks …
Is Precise Recovery Necessary? A Task-Oriented Imputation Approach for Time Series Forecasting on Variable Subset
Variable Subset Forecasting (VSF) refers to a unique scenario in multivariate time series
forecasting, where available variables in the inference phase are only a subset of the …
forecasting, where available variables in the inference phase are only a subset of the …