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Found 3 papers, 2 papers with code
Hybrid Neural Representations for Spherical Data
In this paper, we study hybrid neural representations for spherical data, a domain of increasing relevance in scientific research.
A Simple and Scalable Representation for Graph Generation
Recently, there has been a surge of interest in employing neural networks for graph generation, a fundamental statistical learning problem with critical applications like molecule design and community analysis.
Graph Generation with $K^2$-trees
Generating graphs from a target distribution is a significant challenge across many domains, including drug discovery and social network analysis.
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