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05/23/2023
To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion
Embedding models have shown great power in knowledge graph completion (K...
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02/28/2023
DC-Former: Diverse and Compact Transformer for Person Re-Identification
In person re-identification (re-ID) task, it is still challenging to lea...
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11/12/2022
Self-Supervised Graph Structure Refinement for Graph Neural Networks
Graph structure learning (GSL), which aims to learn the adjacency matrix...
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10/26/2022
Learning on Large-scale Text-attributed Graphs via Variational Inference
This paper studies learning on text-attributed graphs (TAGs), where each...
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10/17/2022
Test-Time Training for Graph Neural Networks
Graph Neural Networks (GNNs) have made tremendous progress in the graph ...
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02/16/2022
HousE: Knowledge Graph Embedding with Householder Parameterization
The effectiveness of knowledge graph embedding (KGE) largely depends on ...
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12/09/2021
HBReID: Harder Batch for Re-identification
Triplet loss is a widely adopted loss function in ReID task which pulls ...
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12/08/2021
Adaptive Kernel Graph Neural Network
Graph neural networks (GNNs) have demonstrated great success in represen...
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10/25/2021
Gophormer: Ego-Graph Transformer for Node Classification
Transformers have achieved remarkable performance in a myriad of fields ...
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11/23/2020