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Found 9 papers, 8 papers with code
Open-World Social Event Classification
To tackle these challenges, we propose an Open-World Social Event Classifier (OWSEC) model in this paper.
MMT: Image-guided Story Ending Generation with Multimodal Memory Transformer
Finally, a multimodal transformer decoder constructs attention among multimodal features to learn the story dependency and generates informative, reasonable, and coherent story endings.
Ranked #1 on
Image-guided Story Ending Generation
on LSMDC-E
Integrating multi-label contrastive learning with dual adversarial graph neural networks for cross-modal retrieval
To date, most of the existing techniques mainly convert multimodal data into a common representation space where similarities in semantics between samples can be easily measured across multiple modalities.
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering
Based on a Markov process that trades off two types of distances, we present Markov Graph Diffusion Collaborative Filtering (MGDCF) to generalize some state-of-the-art GNN-based CF models.
Ranked #2 on
Recommendation Systems
on Gowalla
Contrastive Adaptive Propagation Graph Neural Networks for Efficient Graph Learning
Recently the field has advanced from local propagation schemes that focus on local neighbors towards extended propagation schemes that can directly deal with extended neighbors consisting of both local and high-order neighbors.
GRecX: An Efficient and Unified Benchmark for GNN-based Recommendation
In this paper, we present GRecX, an open-source TensorFlow framework for benchmarking GNN-based recommendation models in an efficient and unified way.
Adaptive label-aware graph convolutional networks for cross-modal retrieval
Firstly, we construct an instance representation learning branch to transform instances of different modalities into a common representation space.
Dual adversarial graph neural networks for multi-label cross-modal retrieval
To date, most existing methods transform multimodal data into a common representation space where semantic similarities between items can be directly measured across different modalities.
Efficient Graph Deep Learning in TensorFlow with tf_geometric
We introduce tf_geometric, an efficient and friendly library for graph deep learning, which is compatible with both TensorFlow 1. x and 2. x.
