118 citations · 440 across the 36 of their papers we have counts for
4 papers · 1 filter
Graph Neural Networks Powered by Encoder Embedding for Improved Node Learning
Shiyu Chen, Cencheng Shen, Youngser Park +1
Graph neural networks (GNNs) have emerged as a powerful framework for a wide range of node-level graph learning tasks. However, their performance typically depends on random or min…
Statistical inference on black-box generative models in the data kernel perspective space
Hayden Helm, Aranyak Acharyya, Brandon Duderstadt +2
Generative models are capable of producing human-expert level content across a variety of topics and domains. As the impact of generative models grows, it is necessary to develop s…
Leveraging semantically similar queries for ranking via combining representations
Hayden S. Helm, Marah Abdin, Benjamin D. Pedigo +8
In modern ranking problems, different and disparate representations of the items to be ranked are often available. It is sensible, then, to try to combine these representations to…
Distance-based Positive and Unlabeled Learning for Ranking
Hayden S. Helm, Amitabh Basu, Avanti Athreya +12
Learning to rank -- producing a ranked list of items specific to a query and with respect to a set of supervisory items -- is a problem of general interest. The setting we consider…