Guido Walter Di Donato, PhD
@gwdidonatoCEO & Co-Founder @GenoGra Postdoctoral researcher @necst - PoliMi Ph.D. in Information Technology @necst Bioengineer @ PoliMi and UIC.
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Alberto Parravicini
@AlbertoParravicini
Georgi Gerganov
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Jouni Siren
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Jason Chin
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Heng Li
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Experimental results on runtime performances of KGE methods, performed through the KGE-Perf framework. The framework and the obtained results are described in: A.S. Valeriani, G.W. Di Donato and M.D. Santambrogio, “Exploring the runtime performance of knowledge graph embedding methods”, in 2021 IEEE6th International Forum on Research and Technology for Society and Industry (RTSI) (IEEE RTSI 2021), Napoli, Italy, Sep. 2021.
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AStarix: Fast and Optimal Sequence-to-Graph Aligner
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