Toward a Manifold-Preserving Temporal Graph Network in Hyperbolic Space
Authors: Viet Quan Le, Viet Cuong Ta
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | By evaluating on diverse real-world dynamic graphs, our model has achieved significant improvements in link prediction and new link prediction tasks, in comparison with other baselines. |
| Researcher Affiliation | Academia | Viet Quan Le and Viet Cuong Ta Human Machine Interaction Laboratory, VNU University of Engineering and Technology, Hanoi, Vietnam {quanle9211@gmail.com, cuongtv@vnu.edu.vn} |
| Pseudocode | Yes | Algorithm 1 HMPTGN learning process |
| Open Source Code | Yes | Our implementation is available at the github repository https://github.com/quanlv9211/HMPTGN. |
| Open Datasets | Yes | We evaluate our model and other baselines on 6 datasets: email communication networks Enron [Klimt and Yang, 2004]; academic co-author networks (COLAB) [Yang and Leskovec, 2012]; private messaging network system among students (UCI) [Panzarasa et al., 2009]; synthetic dataset based on the SIR disease spreading model (Disease) [Bjørnstad et al., 2002]; interactions network on the Math Overflow website (MO) [Paranjape et al., 2016]; social network graph of Facebook Wall posts (FB) [Yang et al., 2021]. |
| Dataset Splits | No | We choose the last k snapshots as the test set and the rest as the training set. The paper does not explicitly mention a separate validation set split or its details. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | No | The paper does not contain specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) in the main text. |