In many intelligent transportation systems, predicting the future motion of heterogeneous traffic participants is a fundamental but challenging task due to various factors encompassing the agents’ dynamic states, interactions with neighboring agents and surrounding traffic infrastructures, and their stochastic and multi-modal natural behavior tendencies. However, existing approaches have ...

2021年9月1日 · HHGN combines multiple features of entity, sentence as well as context for evidence representation, and employs a heterogeneous graph to capture their semantic relations. Inspired by the human inference process, we design a hierarchical reasoning-based node updating strategy to propagate the evidence features.

2024年10月7日 · In HHGNN, we define the hypergraph convolutional neural networks in hyperbolic space. Furthermore, considering the multimodal nature of data representations, our model demonstrates strong scalability, currently supporting over ten data formats and capable of constructing hypergraph inputs for HHGNN training.

【September 11, 2024】The modified code now supports the latest versions of torch and DGL. --Please run train.py to train the HHGNN in NYC city. Due to the huge number of hyperedges, …

Easy-to-Use: OpenHGNN provides easy-to-use interfaces for running experiments with the given models and dataset. Besides, we also integrate optuna to get hyperparameter optimization. …

Paper: Hierarchical Heterogeneous Graph Network based Multimodal Emotion Recognition in Conversation. If you want to download the MELD database, you can access the link: …

2021年9月1日 · HHGN combines multiple features of entity, sentence as well as context for evidence representation, and employs a heterogeneous graph to capture their semantic relations. Inspired by the human inference process, we design a hierarchical reasoning-based node updating strategy to propagate the evidence features.

2021年12月30日 · To facilitate robust and reproducible HGNN research, we construct the Heterogeneous Graph Benchmark (HGB), consisting of 11 diverse datasets with three tasks. HGB standardizes the process of heterogeneous graph data splits, feature processing, and performance evaluation.

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2021年9月1日 · Our research goal in this paper is to develop a fact verification model which can leverage multi-granularity semantic units and capture their relations for evidence representation, as well as present the explainability in the evidence reasoning process. Hence, we propose a Hierarchical Reasoning-based Heterogeneous Fig. 1. 1.