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cs.LG2019
SENSE: Semantically Enhanced Node Sequence Embedding
Swati Rallapalli, Liang Ma, Mudhakar Srivatsa +4
Effectively capturing graph node sequences in the form of vector embeddings is critical to many applications. We achieve this by (i) first learning vector embeddings of single grap…
cs.LG2019
neuralRank: Searching and ranking ANN-based model repositories
Nirmit Desai, Linsong Chu, Raghu K. Ganti +2
Widespread applications of deep learning have led to a plethora of pre-trained neural network models for common tasks. Such models are often adapted from other models via transfer…