GraphML News (11.11.22)

This week was dominated by molecular ML and drug discovery events:

- Broad Institute published a YouTube playlist of talks from the recent Machine Learning and Drug Discovery Symposium and leading drug discovery researchers.

- ELLIS Machine Learning for Drug Discovery Workshop will take place online in Zoom and GatherTown on Nov 28th, registration is free!

- Valence Discovery launched a blog platform for Drug Discovery related posts, the inaugural post by Clemens Isert talks about Quantum ML for drug-like molecules.

And a new work from GemNet authors: How robust are modern graph neural network potentials in long and hot molecular dynamics simulations? The work supports a recent line of works (see the Halloween post) on ML force fields particularly focusing on hot dynamics where low test MAE does not necessarily correspond to good simulations. The most important robustness factor seems to be more training data!