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Found 6 papers, 3 papers with code
Pretraining Language Models with Text-Attributed Heterogeneous Graphs
In many real-world scenarios (e. g., academic networks, social platforms), different types of entities are not only associated with texts but also connected by various relationships, which can be abstracted as Text-Attributed Heterogeneous Graphs (TAHGs).
Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification
Finally, we combine the contextual information of patent texts that contains the semantics of IPC codes, and assignees' sequential preferences to make predictions.
Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction
Finally, the patent application trend is predicted by aggregating the representations of the target company and classification codes from static, dynamic, and hierarchical perspectives.
Quasi-Score Matching Estimation for Spatial Autoregressive Model with Random Weights Matrix and Regressors
With the rapid advancements in technology for data collection, the application of the spatial autoregressive (SAR) model has become increasingly prevalent in real-world analysis, particularly when dealing with large datasets.
Cooperative guidance of multiple missiles: a hybrid co-evolutionary approach
Cooperative guidance of multiple missiles is a challenging task with rigorous constraints of time and space consensus, especially when attacking dynamic targets.
Sensitivity-based dynamic performance assessment for model predictive control with Gaussian noise
To this end, a sensitivity-based performance assessment approach is proposed to pre-evaluate the dynamic economic and tracking performance of them in this work.
