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Found 3 papers, 2 papers with code
AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators
Most of the existing contrastive learning methods employ pre-defined view generation methods, e. g., node drop or edge perturbation, which usually cannot adapt to input data or preserve the original semantic structures well.
BM-NAS: Bilevel Multimodal Neural Architecture Search
Deep neural networks (DNNs) have shown superior performances on various multimodal learning problems.
Learning to Generate Diverse Dance Motions with Transformer
We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods.
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