1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.GR2026
Random-Forest-Induced Graph Neural Networks for Tabular Learning
Haozhe Chen, Soheila Farokhi, Kelvyn Bladen +2
Graphs are essential for modeling complex relationships and capturing structured interactions in data. Graph Neural Networks (GNNs) are particularly effective when such relational…
stat.ML2024★ 1 cited
Training-Free Guidance for Discrete Diffusion Models for Molecular Generation
Thomas J. Kerby, Kevin R. Moon
Training-free guidance methods for continuous data have seen an explosion of interest due to the fact that they enable foundation diffusion models to be paired with interchangable…
cs.LG2024
Exploring higher-order neural network node interactions with total correlation
Thomas Kerby, Teresa White, Kevin Moon
In domains such as ecological systems, collaborations, and the human brain the variables interact in complex ways. Yet accurately characterizing higher-order variable interactions…