2 papers
cs.LG2022
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators
Jenna A. Bilbrey, Kristina M. Herman, Henry Sprueill +6
The demonstrated success of transfer learning has popularized approaches that involve pretraining models from massive data sources and subsequent finetuning towards a specific task…
cs.LG2022
Tuple Packing: Efficient Batching of Small Graphs in Graph Neural Networks
Mario Michael Krell, Manuel Lopez, Sreenidhi Anand +2
When processing a batch of graphs in machine learning models such as Graph Neural Networks (GNN), it is common to combine several small graphs into one overall graph to accelerate…