Search Results for author: Jakob Hansen

Found 5 papers, 2 papers with code

Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding

1 code implementation7 Oct 2021 Thomas Gebhart, Jakob Hansen, Paul Schrater

Knowledge graph embedding involves learning representations of entities -- the vertices of the graph -- and relations -- the edges of the graph -- such that the resulting representations encode the known factual information represented by the knowledge graph and can be used in the inference of new relations.

Knowledge Graph Embedding

Sheaf Neural Networks

no code implementations NeurIPS Workshop TDA_and_Beyond 2020 Jakob Hansen, Thomas Gebhart

We present a generalization of graph convolutional networks by generalizing the diffusion operation underlying this class of graph neural networks.

Toward a Spectral Theory of Cellular Sheaves

1 code implementation4 Aug 2018 Jakob Hansen, Robert Ghrist

This paper outlines a program in what one might call spectral sheaf theory --- an extension of spectral graph theory to cellular sheaves.

Algebraic Topology Combinatorics 55N30, 05C50

Consistency constraints for overlapping data clustering

no code implementations15 Aug 2016 Jared Culbertson, Dan P. Guralnik, Jakob Hansen, Peter F. Stiller

We examine overlapping clustering schemes with functorial constraints, in the spirit of Carlsson--Memoli.


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