← Search

Andrew W Fitzgibbon

2 accepted papers

2024

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets

ICLR 2024poster

Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and hence typically small, the lack of datasets with labeled features, and codebases to manage those datasets, has hindered…

2023

Generating QM1B with PySCF$_{\text{IPU}}$

NeurIPS 2023poster

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 with billions of training examples. Similar benefits are yet to be unlocked for quantum chemistry, where the potential o…

Cited by 0SourcePDFScholar