Senior Researcher at Microsoft Research AI for Science. Previously Oxford PhD in machine learning
London, England
Joined November 2014
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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! arxiv.org/abs/2506.19960
Adam Foster retweeted
Last call - open til Oct 30!
Are you excited about #MachineLearning and developing new architectures for Molecular Biology? Joint us for the next chapter of BioEmu at @MSFTResearch AI for Science - Berlin DE or Cambridge UK.
aka.ms/bioemu-ml
Adam Foster retweeted
Want to join our BioEmu team in @MSFTResearch AI for Science as an Intern? Berlin DE or Cambridge UK are available. Preference for candidates at the end of their PhDs, but open for everything:
jobs.careers.microsoft.com/g…
BioEmu now published in @ScienceMagazine !!
What is BioEmu? Check out this video:
youtu.be/LStKhWcL0VE?si=tQQX…
Adam Foster retweeted
I have an opening for a 2-year postdoc in probabilistic machine learning and/or experimental design. The application deadline is the 3rd of September. See here for details and how to apply: tinyurl.com/rainmlpostdoc202…
It's a great achievement for the team and for @FrankNoeBerlin who was at the helm throughout!
BioEmu now published in @ScienceMagazine !!
What is BioEmu? Check out this video:
youtu.be/LStKhWcL0VE?si=tQQX…
Adam Foster retweeted
There’s a lot of confusion around uncertainty in machine learning.
We argue the "aleatoric vs epistemic" view has contributed to this and present a rigorous alternative.
#ICML2025 with @janundnik @eleanortrollope @markvanderwilk @adamefoster @tom_rainforth
1/5
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 ae-foster.github.io/posts/20… (3/n)
Adam Foster retweeted
The aleatoric-epistemic view on uncertainty doesn't serve ML researchers' needs and should be replaced.
Come to the talk and poster tomorrow (Sat 14 Dec) at the #NeurIPS2024 workshop on Bayesian decisions (gp-seminar-series.github.io/…).
openreview.net/forum?id=WIjg…
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.
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Adam Foster retweeted
Interested in working with a highly collaborative, interdisciplinary team to push the state of the art of generative AI for materials design? Join us as an intern by applying through this link! We are the team behind the MatterGen and MatterSim models from Microsoft Research AI for Science.
jobs.careers.microsoft.com/g…