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Found 3 papers, 2 papers with code
Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning
Hence, this work proposes a new principle for unsupervised graph representation learning: Graph-wise Common latent Factor EXtraction (GCFX).
GL-Disen: Global-Local disentanglement for unsupervised learning of graph-level representations
Our work is the first to study disentanglement learning for graph-level representations.
Attention-Based Context Aware Reasoning for Situation Recognition
However, existing query-based reasoning methods have not considered handling of inter-dependent queries which is a unique requirement of semantic role prediction in SR.
Ranked #8 on
Situation Recognition
on imSitu
Fine-grained Action Recognition
Grounded Situation Recognition
+3
