most citedGPS++: Reviving the Art of Message Passing for Molecular Property Prediction

2 citations · 2 across the 1 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2023

Generating QM1B with PySCF

Alexander Mathiasen, Hatem Helal, Kerstin Klaser +6

The emergence of foundation models in Computer Vision and Natural Language Processing have resulted in immense progress on downstream tasks. This progress was enabled by datasets w…

cs.LG2023★ 2 cited

GPS++: Reviving the Art of Message Passing for Molecular Property Prediction

Dominic Masters, Josef Dean, Kerstin Klaser +9

We present GPS++, a hybrid Message Passing Neural Network / Graph Transformer model for molecular property prediction. Our model integrates a well-tuned local message passing compo…