iiinova — where your digital self keeps evolving

Reposted by Jigyasa Nigam

COSMO Lab @labcosmo.bsky.social · 03/04/2025

As a bonus - it also works in the condensed phase, and there's a #recipe for this atomistic-cookbook.org/examples/per... 😋

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Reposted by Jigyasa Nigam

COSMO Lab @labcosmo.bsky.social · 03/04/2025

When you combine #machinelearning and #compchem, you need to start worrying at the QM details within your ML architecture. We use our indirect Hamiltonian framework and pySCFAD to explore the enormous design space arxiv.org/abs/2504.01187

A schematic of the functioning of a ML/QM hybrid framework

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Reposted by Jigyasa Nigam

Frank Noe @franknoe.bsky.social · 21/02/2025

Today we have published BioEmu-Benchmarks (MIT license): a code to evaluate the multi-conformation sampling benchmarks, MD free energy landscape benchmarks, and folding free energy benchmarks shown in the BioEmu-1 paper with BioEmu or your own model. Some details below 🧵 github.com/microsoft/bi...

github.com

GitHub - microsoft/bioemu-benchmarks: Benchmarking code accompanying the release of `bioemu`

Benchmarking code accompanying the release of `bioemu` - microsoft/bioemu-benchmarks

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Jigyasa Nigam @jnigam.bsky.social · 16/02/2025

So great to be back home at #EPFL for AMLD @appliedmldays.bsky.social ‬earlier this week, missing @micheleceriotti.bsky.social! Also was an opportunity to get up to mischief and catch up on some science with the @labcosmo.bsky.social gang!

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Reposted by Jigyasa Nigam

Frank Noe @franknoe.bsky.social · 06/12/2024

Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science. www.biorxiv.org/content/10.1...

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