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Thorben Frank

@thorbenfrank

Postdoctoral Researcher @ TU Berlin @BIFOLD Berlin | AI for molecular simulations

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21.11.2024
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Latest posts by Thorben Frank @thorbenfrank

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Ever get tired of tiny timesteps bottlenecking your MD simulations?

We show how to train a model for large-timestep Hamiltonian dynamics directly on standard MLFF datasets. ๐—ก๐—ผ ๐—ฟ๐—ฒ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐˜๐—ฟ๐—ฎ๐—ท๐—ฒ๐—ฐ๐˜๐—ผ๐—ฟ๐—ถ๐—ฒ๐˜€, ๐—ป๐—ผ ๐˜‚๐—ป๐—ฟ๐—ผ๐—น๐—น๐—ถ๐—ป๐—ด, ๐—ป๐—ผ ๐˜๐—ฒ๐—ฎ๐—ฐ๐—ต๐—ฒ๐—ฟ needed!

๐Ÿงต๐Ÿ‘‡

19.02.2026 15:05 ๐Ÿ‘ 18 ๐Ÿ” 8 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 2

thank you @adrianhill.de! Complex problems require easy solutions!

05.12.2025 07:11 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

If you ever wondered about the pros and cons of Euclidean symmetries in generative models for molecules, stop by at our #NeurIPS poster on Thursday morning ๐Ÿงฌ #AI4Science

29.11.2025 15:21 ๐Ÿ‘ 2 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0

SO3LR is now published in @jacs.acspublications.org โ˜€๏ธ

Itโ€™s a pre-trained #ML #forcefield, applicable to #proteins, #glycoproteins and #lipids in explicit water or vacuo. ๐Ÿงฌ

Test it right now and run you own simulations
๐Ÿ‘‰ github.com/general-mole...

#AI4Science #MachineLearning

08.09.2025 13:14 ๐Ÿ‘ 5 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Introductory Statistical Mechanics - YouTube CHM328 lectures given at UofT in winter 2025

The room I was given to teach #PhysicalChemistry @uoft.bsky.social has no chalkboards ๐Ÿ˜ฑ - o tempora, o mores! But then I can just as well record and share my lectures here: youtube.com/playlist?lis...

17.01.2025 23:40 ๐Ÿ‘ 11 ๐Ÿ” 2 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0
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Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needsโ€”like efficient solar cells or CO2 recyclingโ€”advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...

16.01.2025 10:07 ๐Ÿ‘ 62 ๐Ÿ” 26 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 12
Euclidean Fast Attention: Machine Learning Global Atomic Representations at Linear Cost Long-range correlations are essential across numerous machine learning tasks, especially for data embedded in Euclidean space, where the relative positions and orientations of distant components are o...

Excited to share our latest work on Euclidean fast attention, which enables learning global atomic representations at linear cost! ๐Ÿ”ฅ

The representations describe the distance and orientation between atoms, crucial for modeling molecular systems

tinyurl.com/47xud8nr

#MachineLearning #AI4Science

03.01.2025 20:50 ๐Ÿ‘ 8 ๐Ÿ” 2 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 1

would be great if you can add me as well. Thanks :-)

03.12.2024 18:21 ๐Ÿ‘ 1 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

The first list filled up, so here's a second list of AI for Science researchers on bluesky.

Let me know if I missed you / if you'd like to join!

bsky.app/starter-pack...

20.11.2024 08:56 ๐Ÿ‘ 70 ๐Ÿ” 29 ๐Ÿ’ฌ 58 ๐Ÿ“Œ 0

would like to be added as well. Thx :-)

28.11.2024 21:28 ๐Ÿ‘ 1 ๐Ÿ” 0 ๐Ÿ’ฌ 1 ๐Ÿ“Œ 0

I think @ssnio.bsky.social is missing :-)

28.11.2024 14:02 ๐Ÿ‘ 1 ๐Ÿ” 0 ๐Ÿ’ฌ 0 ๐Ÿ“Œ 0