User profiles for Xovee Xu
Xovee XuPhD Candidate, UESTC, 徐增 Verified email at std.uestc.edu.cn Cited by 848 |
A survey of information cascade analysis: Models, predictions, and recent advances
The deluge of digital information in our daily life—from user-generated content, such as
microblogs and scientific papers, to online business, such as viral marketing and advertising—…
microblogs and scientific papers, to online business, such as viral marketing and advertising—…
Spatial-temporal contrasting for fine-grained urban flow inference
Fine-grained urban flow inference (FUFI) problem aims to infer the fine-grained flow maps
from coarse-grained ones, benefiting various smart-city applications by reducing electricity, …
from coarse-grained ones, benefiting various smart-city applications by reducing electricity, …
Learning latent seasonal-trend representations for time series forecasting
Forecasting complex time series is ubiquitous and vital in a range of applications but
challenging. Recent advances endeavor to achieve progress by incorporating various deep …
challenging. Recent advances endeavor to achieve progress by incorporating various deep …
Learning spatiotemporal manifold representation for probabilistic land deformation prediction
Landslides refer to occurrences of massive ground movements due to geological (and
meteorological) factors, and can have disastrous impacts on property, economy, and even lead to …
meteorological) factors, and can have disastrous impacts on property, economy, and even lead to …
Casflow: Exploring hierarchical structures and propagation uncertainty for cascade prediction
Understanding in-network information diffusion is a fundamental problem in many applications
and one of the primary challenges is to predict the information cascade size. Most of the …
and one of the primary challenges is to predict the information cascade size. Most of the …
CCGL: Contrastive cascade graph learning
Supervised learning, while prevalent for information cascade modeling, often requires
abundant labeled data in training, and the trained model is not easy to generalize across tasks …
abundant labeled data in training, and the trained model is not easy to generalize across tasks …
Dynamic Transformer ODEs for large-scale reservoir inflow forecasting
Forecasting incoming water demand is a critical step in efficient reservoir management and
revenue optimization in large-scale cascade hydropower stations. It depends on multiple …
revenue optimization in large-scale cascade hydropower stations. It depends on multiple …
Counterfactual graph learning for anomaly detection on attributed networks
Graph anomaly detection is attracting remarkable multidisciplinary research interests ranging
from finance, healthcare, and social network analysis. Recent advances on graph neural …
from finance, healthcare, and social network analysis. Recent advances on graph neural …
Retrieval-augmented hypergraph for multimodal social media popularity prediction
Accurately predicting the popularity of multimodal user-generated content (UGC) is
fundamental for many real-world applications such as online advertising and recommendation. …
fundamental for many real-world applications such as online advertising and recommendation. …
Information cascade popularity prediction via probabilistic diffusion
Information cascade popularity prediction is an important problem in social network content
diffusion analysis. Various facets have been investigated (eg, diffusion structures and …
diffusion analysis. Various facets have been investigated (eg, diffusion structures and …