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!

RT @tom_rainforth: I have an opening for a 2-year postdoc in probabilistic machine learning and/or experimental design. The application de….

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I feel fortunate to have been able to contribute to the effort.

It's a great achievement for the team and for @FrankNoeBerlin who was at the helm throughout!.

RT @fbickfordsmith: There’s a lot of confusion around uncertainty in machine learning. We argue the "aleatoric vs epistemic" view has cont….

Huge thanks to Zeno Schätzle, @PBerntSzab1, .@SherryLixueC, @jonkhler, @n_gao96 , Gino Cassella, Jiawei Li, @FrankNoeBerlin and Jan Hermann.(2/n).

Digging into the model we found intriguing behaviour, such as the unsupervised discovery by the model of ‘core’ electron orbitals for second row atoms. This has been a fascinating project to be a part of! Check out the preprint for more details and results. (8/n)

We also saw very strong results confirming the experimental activation energy of a Diels-Alder reaction, and significantly outperforming earlier transferable QMC approaches (7/n).

We scaled this idea up and pushed it to work on strongly correlated systems. On a cost/error plot, we find that Orbformer is on or ahead of the Pareto frontier formed by traditional multireference methods, a first for deep QMC. (6/n)

To get cost down we make use of amortization: solving a single minimization problem with a more complex network that represents multiple wavefunctions simultaneously (5/n)

Describing strongly correlated quantum systems remains a major challenge in quantum chemistry. Deep QMC offer a potential solution, but at a huge computational cost. (4/n).

For a short ML-focused introduction to this paper, I wrote a short blog post (3/n).

RT @fbickfordsmith: The aleatoric-epistemic view on uncertainty doesn't serve ML researchers' needs and should be replaced. Come to the ta….

BIG opportunities to join @MSFTResearch AI for science: one senior researcher and one RSDE position, both focused on applications in molecular biology with the awesome @FrankNoeBerlin. Cambridge, UK or Berlin, DE.

RT @xie_tian: Interested in working with a highly collaborative, interdisciplinary team to push the state of the art of generative AI for m….

RT @desirivanova: Excited to share that I recently defended my DPhil 🎉. Huge thanks to my supervisors @tom_rainforth and @yeewhye, all my c….

Curious what I've been working on since joining AI for science? With an incredible, multidisciplinary team we've studied the 'wave function -> election density' marginalisation using score matching & NCE. This has some big gains over older Gaussian-based methods.

RT @tom_rainforth: I have an opening for a 2.5-year postdoc position in the RainML lab as part of my ERC grant on probabilistic machine lea….

RT @ikwess: Whoa, Aurora is featured in a Nature news article!. We believe that forecasting atmospheric chemistry is only the beginning of….

RT @crisbodnar: Thrilled to share what we have been working on for the past year. Aurora is a major step forward towards a foundation model….