127 citations · 129 across the 3 of their papers we have counts for
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cs.LG2022★ 127 cited
Representing Long-Range Context for Graph Neural Networks with Global Attention
Zhanghao Wu, Paras Jain, Matthew A. Wright +3
Graph neural networks are powerful architectures for structured datasets. However, current methods struggle to represent long-range dependencies. Scaling the depth or width of GNNs…
cs.LG2021★ 2 cited
Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines
Matthew A. Wright, Joseph E. Gonzalez
Despite their ubiquity in core AI fields like natural language processing, the mechanics of deep attention-based neural networks like the Transformer model are not fully understood…