Hypertron: Explicit Social-Temporal Hypergraph Framework for Multi-Agent Forecasting
Authors: Yu Tian, Xingliang Huang, Ruigang Niu, Hongfeng Yu, Peijin Wang, Xian Sun
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments on several challenging real-world trajectory forecasting datasets show that Hypertron outperforms a wide array of stateof-the-art methods while saving over 60% parameters and reducing 30% inference time. |
| Researcher Affiliation | Academia | 1Key Laboratory of Network Information System Technology, Aerospace Information Research Institute, Chinese Academy of Sciences 2 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences |
| Pseudocode | No | The paper does not contain a clearly labeled pseudocode or algorithm block. |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code for the described methodology or a link to a code repository. |
| Open Datasets | Yes | To evaluate our methods, we conduct experiments on three publicly examined datasets: The ETH/UCY datasets and the Stanford Drone Dataset. |
| Dataset Splits | No | The paper does not specify exact train/validation/test split percentages or sample counts for the datasets. |
| Hardware Specification | Yes | To measure the inference time, we use a V100 GPU. |
| Software Dependencies | No | The paper mentions using 'Adam optimizer' but does not specify software dependencies with version numbers (e.g., Python, PyTorch, CUDA versions). |
| Experiment Setup | Yes | We train the Hypertron with Adam optimizer, and the initial learning rate is 0.001. The number of hyperedges in the social hypergraph is set to 32, and each hyperedge ei s indicates the social correlation of the i-th agent with others. Similarly, the counterpart of the temporal hypergraph is set to 20, and each ej t indicates the temporal correlation of the agent in the j-th timestep with others. |