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Nicholas Gao

@n-gao.bsky.social

PhD Student @TU_Munich Machine Learning for Quantum Chemistry Former: Intern @MSFTResearch AI4Science & Intern @NasaAmes

10 Posts313 Follower69 Folgt
@sophie-xhonneux.bsky.social · 11mo ago

Blog Posts are a great medium to share ML research. If you have new intuitions on past work, noticed key implementation details for reproducibility, have insights into the societal implications of AI, or an interesting negative result consider writing and submitting a blogpost.

Adam Foster@adamefoster.bsky.social · last yr.

I am very happy to share Orbformer, a foundation model for wavefunctions using deep QMC that offers a route to tackle strongly correlated quantum states! arxiv.org/abs/2506.19960 (1/n)

An ab initio foundation model of wavefunctions that accurately describes chemical bond breaking

Reliable description of bond breaking remains a major challenge for quantum chemistry due to the multireferential character of the electronic structure in dissociating species. Multireferential method...

arxiv.org

Nicholas Gao@n-gao.bsky.social · last yr.

I am truly excited to share our latest work with @mscherbela.bsky.social, Philipp Grohs, and @guennemann on "Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems"! arxiv.org/abs/2504.06087

Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems

We present finite-range embeddings (FiRE), a novel wave function ansatz for accurate large-scale ab-initio electronic structure calculations. Compared to contemporary neural-network wave functions, Fi...

arxiv.org