Looking forward to an exciting talk by Simon Mathis about BioML & Sustainability!

Experiment-driven atomistic materials modeling. MLPs and on-the-fly ML-XPS prediction generate atomistic structures that match the experimental XPS. On arXiv: arxiv.org/abs/2402.03219 Esp. thanks to Tigany Zarrouk, as well as Rina Ibragimova, Albert Bartok-Partay, Suomen Akatemia | Research Council of Finland, CSC

Matthias Wissuwa Rheinische Friedrich-Wilhelms-Universität Bonn PhenoRob presents new variety 'Mavitrika' which strives in Madagascar's low phosphorus conditions and shows increased zinc in the grain in presence of Madagascar's prime minister Christian Louis Ntsay and ministers of Agriculture and Higher Education

Curious what’s hard about non-compact group equivariance? Interested in ML for polynomial optimization? Come to Mitchell Harris' and my poster #275 on Friday morning, 10:45am - 12:45pm, to learn more (including a surprising impossibility result)! Paper: openreview.net/pdf?id=gyfXuRf…

Excited for #ICLR with Ilyes Batatia and Felix Faber. Come checkout Matrix Functions NN tomorrow or DM to have a chat. See how we outperform global attention to capture structured non-locality. 😎 Spotlight: tomorrow 10:45 (Halle B) Updated paper: arxiv.org/pdf/2310.10434

Come with us about enzyme engineering with AI and ultra high throughput screening at our poster at GEMBio Workshop at #ICLR2024 with Maximilian Gantz

Excited to share a new update to gRNAde code! github.com/chaitjo/geomet… You can now forward-fold designed RNAs in 2D and 3D (RhoFold) to measure structural self-consistency metrics + cool visualisations! Hope we develop our own version of 'designability' in the RNA world ;)

First ever ab-initio solvation free energies AND they match experiment 🤯. Super cool stuff by Harry Moore!

There's been many new Geometric GNNs in the past couple weeks combining 3D equivariance and topological ideas (simplices, cells). I think folks should really try their best to compare to MACE (arxiv.org/abs/2206.07697), if possible, b/c its a way to get similar capabilities.

Honored to have been part of the TechScale workshop on single-atom catalysis. Thanks for the invitation to talk about ML force fields for heterogenous catalysis. And thank you for all the inspiring talks by Gianfranco Pacchioni, michal otyepka, TBenešová and others.

There's lots of choice out there of for algorithms to perform simulations at constant-temperature 🌡️. If you want to make an informed choice, there's now a #cookbook recipe ready to try 🧑‍🍳 atomistic-cookbook.org/examples/therm…

Check out OMat24 for inorganic materials! I'm super excited to see what the community does next with this dataset and models. Get in touch if you have questions or feedback!

Generative models often create molecules that are hard to synthesize. Tomorrow, we present SynFlowNet, a GFlowNet designed to generate synthesizable molecules using documented reactions and purchasable materials. Learn more at the MLSB workshop: arxiv.org/abs/2405.01155

Come checkout *BoostMD*, a new approach for accelerating machine learning force fields, by leveraging infromation from previous time steps. Today at MLSB @ Neurips (Room E-11). paper: openreview.net/pdf?id=H0USH61…

by what i can only assume was an unlikely chain of events, i was asked to serve as associate editor on the editorial board of IOP's new "AI for Science" journal (iopscience.iop.org/journal/3050-2…) that launched this week. i was asked to offer some guidance and actively solicit manuscripts

Super practical tool for placing adsorbates on surfaces! Quick and exhaustive. Great to see it out Edvin Fako

Matbench Discovery is out in Nature Machine Intelligence @ Paper: rdcu.be/esRFB Leaderboard: …tbench-discovery.materialsproject.org No better time to thank all my co-authors Rhys Goodall, Philipp Benner, Yuan Chiang Yuan (Cyrus) Chiang, Bowen Deng, Mark Asta, Gerbrand Ceder Ceder Group,

Check out La-Proteina, our new model for all-atom structure generation at scale! Was a very fun project to work on with Tomas Geffner and the rest of the team. Two things I am particularly excited about in 🧵 1/n