9 citations · 12 across the 5 of their papers we have counts for
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cs.LG2023
Half-Hop: A graph upsampling approach for slowing down message passing
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor +6
Message passing neural networks have shown a lot of success on graph-structured data. However, there are many instances where message passing can lead to over-smoothing or fail whe…
cs.LG2022★ 9 cited
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration
Stefan Abi-Karam, Yuqi He, Rishov Sarkar +3
Graph neural networks (GNNs) have recently exploded in popularity thanks to their broad applicability to ubiquitous graph-related problems such as quantum chemistry, drug discovery…