17 citations · 21 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 4 cited
Globally Interpretable Graph Learning via Distribution Matching
Yi Nian, Yurui Chang, Wei Jin +1
Graph neural networks (GNNs) have emerged as a powerful model to capture critical graph patterns. Instead of treating them as black boxes in an end-to-end fashion, attempts are ari…
cs.LG2019★ 17 cited
AutoML using Metadata Language Embeddings
Iddo Drori, Lu Liu, Yi Nian +5
As a human choosing a supervised learning algorithm, it is natural to begin by reading a text description of the dataset and documentation for the algorithms you might use. We demo…