Topological Preservation in Temporal link prediction
We study the preservation of topological characteristics within the temporal link prediction architectures while proposing a model of our own.
Engineering topics
Publications and source records attributed to Campos, Marco Vinicio.
We study the preservation of topological characteristics within the temporal link prediction architectures while proposing a model of our own.
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Goes over a simple software library (Python) for utilizing sparse autoencoders for more models than just language models.
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Poster presentation for the Student Intern Symposium introducing zig-zag persistence (ZZP) and a minor result showing that a temporal link prediction model was able to create a representation which preserved the dynamic topology of the trained data.
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