Author

Andrew W. Fitzgibbon

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Aug 2026

Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference

Monroe is presented, a new MFM with several innovations over the existing state of the art: increased scale allowing pre-training on over 81 million molecules from the PM6 quantum chemistry dataset; improved graph representation of stereochemistry; improved training losses including conformer denoising and embedding decorrelation; improved multi-task learning; and the use of a prior-data-fitted model (TabPFN) for downstream in-context prediction.

Blazej Banaszewski, Andrew W. Fitzgibbon · 0 citations

#artificial intelligence Preprint Aug 2026

PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints

PGFS++ is introduced, a synthesis-aware reinforcement learning framework for input-specific molecular improvement that improves target properties while preserving high output diversity, and experiments show that PGFS++ improves target properties while preserving high output diversity.

Boqiao Zhang, Godbless James, S. Gottipati et al. · 0 citations