Full Professor of Mathematical Data Science at @univienna and group leader at @oeaw.
Joined May 2021
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Together we will develop machine learning based solvers for PDEs (including the electronic Schrödinger equation in computational chemistry) with CERTIFIED accuracy.
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There are currently openings for two PhD positions in my research group. I am looking for candidates with an excellent background in numerical analysis, scientific computing, machine learning or computational chemistry.
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Philipp Grohs retweeted
📢 @MScherbela, @GrohsPhilipp, @LeonGerard5 and colleagues present an approach that reduces the computational cost to model and compute crystalline materials, such as graphene or lithium hydride, by a factor of 50 compared with previous work. nature.com/articles/s43588-0…
Philipp Grohs retweeted
Fantastic work scaling up neural network VMC methods like FermiNet and Psiformer to previously impossible systems - you can start to tackle real challenging chemistry at this scale!
I am truly excited to share our latest work with @MScherbela, @GrohsPhilipp, and @guennemann on "Accurate Ab-initio Neural-network Solutions to
Large-Scale Electronic Structure Problems"!
arxiv.org/abs/2504.06087
Philipp Grohs retweeted
I am truly excited to share our latest work with @MScherbela, @GrohsPhilipp, and @guennemann on "Accurate Ab-initio Neural-network Solutions to
Large-Scale Electronic Structure Problems"!
arxiv.org/abs/2504.06087