10 citations · 10 across the 2 of their papers we have counts for
3 papers
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…
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Dominique Beaini, Shenyang Huang, Joao Alex Cunha +32
Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and…
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction
Dominic Masters, Josef Dean, Kerstin Klaser +7
This technical report presents GPS++, the first-place solution to the Open Graph Benchmark Large-Scale Challenge (OGB-LSC 2022) for the PCQM4Mv2 molecular property prediction task.…