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Found 4 papers, 2 papers with code
An Exploration of Conditioning Methods in Graph Neural Networks
The flexibility and effectiveness of message passing based graph neural networks (GNNs) induced considerable advances in deep learning on graph-structured data.
Reducing Over-smoothing in Graph Neural Networks Using Relational Embeddings
Graph Neural Networks (GNNs) have achieved a lot of success with graph-structured data.
Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model
The recently released NLLB-200 is a set of multilingual Neural Machine Translation models that cover 202 languages.
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results.
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