good reaction: blog.joss.theoj.org/2026/01/prep...

my long bet to not bother to learn vim commands has finally paid off #sloperator

i may be biased but this is a very nice example of a universal MLIP paper

reality is proving @adrianhill.de more right by the minute -- now all reviews have been reverted to their pre-discussion state. someone remind me why i spent a week+ preparing rebuttals and reading author comments?

ICLR2026 is truly the gift that keeps on giving

When it comes to drama, ICLR 2026 is truly the gift that keeps on giving.

made by a friend of a colleague. iykyk

seems like i was the only ICLR reviewer that bothered to declare LLM usage

This also shows that @typst.app is already a viable alternative to LaTeX for top conferences in ML!

Our paper on XAI + Automatic Differentiation got accepted at #NeurIPS2025. Can't wait to share the camera-ready soon! 🥳

If you are excited about 30x longer time steps in molecular dynamics using FlashMD, but are worried about it not being symplectic, Filippo has something new cooking that should make you even more excited. Head to the #arxiv for a preview arxiv.org/html/2508.01...

for the jax kids, i just made my personal training infra repo public: github.com/sirmarcel/ma... -- happy for some feedback/ideas/takes!

I benefited massively from www.ipam.ucla.edu/programs/lon.... I got into ML for science through that program. Now IPAM may be gone mathstodon.xyz/@tao/1149568...

This, if true, is incredible. A long program in 2011 at IPAM that I attended practically wrote the book on machine learning in materials science, which is now AI. Not funding IPAM would be deeply destructive to US leadership in critical future technologies! Hard to fathom.

✨preprint alert: "learning long-range representations w/ equivariant messages" in which we get into the fray of long-range MLIPs and propose to use equivariant charges w/ classical electrostatics as long-range MP mechanism. we design LOREM, an equivariant MLIP, around this ...

very proud of filippo

Very proud to send Filippo Bigi to Vancouver to give an oral presentation at @icmlconf.bsky.social about our investigation of the use of "dark-side forces" in atomistic simulations. The final version is here openreview.net/forum?id=OEl... and it's worth a read even if you already read the #preprint

So kudos to 🧑‍🚀 Filippo and @marceldotsci.bsky.social bsky.app/profile/labc..., thanks to funders @erc.europa.eu @snf-fns.ch @cscsch.bsky.social and @nccr-marvel.bsky.social, and go to Filippo's talk if you are at #icml25, to see this nice mix of #compchem and #machinelearning!

obvious in hindsight but news to me: accessing np.load-ed arrays by index is orders of magnitude slower than forcing them to RAM. notes.marcel.science/2025/numpy-l...

ok then thanks

very annoying when papers don‘t include raw data for plots

⚡️

🍾

cosmo has joined the universal FF club!

watch out cancer, mihail is coming for you 🔥

Completed my post preprint project: a split keyboard to help with my wrist pain (pictured with the pain-relieving gel it is trying to replace).

anyone at the lausanne applied ML days?

@marceldotsci.bsky.social getting into very dangerous territory.

we're having an interesting seminar next tuesday on equivariance in deep ensembles, for the EPFL squad: actu.epfl.ch/news/seminar...

You think Jacobian and Hessian matrices are prohibitively expensive to compute on your problem? Our latest preprint with @gdalle.bsky.social might change your mind! arxiv.org/abs/2501.17737 🧵1/8

the recording of my talk at orbital materials, together with jonathan schmidt, is out: www.youtube.com/watch?v=0xpR...!

now on day ~2 of debugging bizarre multiprocessing issues with Google Grain, the alleged hot new data loading framework. has anyone here actually used it by any chance?

nice find while back-filling links for tabs.marcel.computer: crosstowntrail.org

non-work account: activated

yum, schnitzel and a lemon

👀

guess i should mention this: as of this month, i’m honoured to receive a walter-benjamin-fellowship from the DFG to fund my stay @labcosmo.bsky.social! i’m very happy this worked out, and look forward to working on the project!

👀

we did some further work on the role of physical priors in machine learning potentials. this time on conservative forces (obtained as gradient of the energy). turns out that not doing that, i.e., direct force prediction, is problematic for simulations! we do some tests & discuss solutions. ✨

leaving this here as a sneak peek for the bluesky crowd… github.com/lab-cosmo/ja...

gave myself a little makeover!

guess time to turn this thing on…