Gregor Lied

CS student @ TU Berlin. ML for molecular simulation @ml_tuberlin.

[Gregor Lied @gregorlied]

Excited to share our latest work on large-timestep molecular dynamics.

[Winfried Ripken @RipkenWinfried]

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. 𝗡𝗼 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘁𝗿𝗮𝗷𝗲𝗰𝘁𝗼𝗿𝗶𝗲𝘀, 𝗻𝗼 𝘂𝗻𝗿𝗼𝗹𝗹𝗶𝗻𝗴, 𝗻𝗼 𝘁𝗲𝗮𝗰𝗵𝗲𝗿 needed!🧵👇

[Gregor Lied @gregorlied]

📄 https://t.co/jbIhrUN5vc

🔗 https://t.co/TgBdZbb95X

📆 Thursday 4 Dec, 11am - 2pm, Exhibit Hall C,D,E #1709

[Gregor Lied @gregorlied]

Heading to @NeurIPSConf in SD!

🚀 We’ll be presenting our latest work, DiTMC - a modular architecture for molecular conformer generation.

🏖️ Excited to meet new and old friends! If you want to grab a coffee and chat about generative models & AI4Science, feel free to reach out.

[Gregor Lied @gregorlied]

🙏 This is a joint work with the amazing @FrankThorben, @RipkenWinfried, Klaus-Robert Müller, Oliver T. Unke and Stefan Chmiela. Thank you so much for this fantastic collaboration!