IEEE

TriDGNet: Triple Feature Encoder-Based Dual Granularity Graph Learning Network for Enhanced Travel Time Estimation

The contemporary urban intelligent transportation system (ITS) generates an enormous amount of trajectory data daily, serving as an essential reflection of traffic dynamics. Accurate estimation of ...
IEEE

Informative Subgraphs Aware Masked Auto-Encoder in Dynamic Graphs

Abstract: Generative self-supervised learning (SSL), especially masked autoencoders (MAE), has greatly succeeded and garnered substantial research interest in graph machine learning. However, the ...
GitHub

Trajectory–User Linking via Heterogeneous Preference Graph and Dual-Encoder Mutual Distillation (HPG-DEMD)

(1) Duration (Days): This represents the total time span of the dataset, calculated as the number of days between the first and the last check-in recorded in the entire dataset. For instance, the ...
Microsoft

Refined graph encoder embedding via self-training and latent community recovery

This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community recovery within ...
GitHub

LSTM-based Sequence-to-Sequence Chatbot

Long Short-Term Memory (LSTM) network with sequence-to-sequence architecture for building conversational chatbots with attention mechanism. lstm-chatbot/ ├── README.md ├── FEATURES.md # Additional ...