This is the PyTorch implementation for LightGCL proposed in the paper LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation, International Conference on Learning Representation, ...
Abstract: Graph representation learning (GRL) is fundamental in multi-graph applications like molecular property prediction. Graph neural networks (GNNs) have emerged as a popular method for GRL.
Abstract: Computer-Aided Design (CAD) sketches, composed of geometric primitives and constraints, are fundamental to CAD models and play a critical role in industrial design and manufacturing.
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