Niklas Rindtorff (@Niklas_TR) header
Niklas Rindtorff (@Niklas_TR) profile picture

PhD student at AITHYRA with @AlexanderTong7

Vienna
Joined September 2015
Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)Photo by Niklas Rindtorff (@Niklas_TR)
Introducing Langevin Flow Maps TLDR: Neural Network Potentials that learn their own stochastic pathwise solution for faster simulation. - Transferable across molecular systems. - Transition dynamics are preserved. - No trajectory data are required. Work together with @sgmccallum, supervised by @AlexanderTong7, and @JamesFosterBath. Arxiv: arxiv.org/abs/2610.05998 Data: huggingface.co/datasets/nikl… Code: github.com/sammccallum/lfm
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Niklas Rindtorff retweeted
Excited to announce the follow-up to our NeurIPS 2026 Oral: Improved Training of Strong Stochastic Flow Maps! We improve the training of SSFMs by unlocking derivative-based losses! Joint work with @antoniofrancaib @rmincam @ChristianKoke @Niklas_TR and @AlexanderTong7
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There is still work left to do. Right now we're only reaching simulation time/wall clock time parity with classical molecular mechanics for large steps and relatively small molecular systems. Enabling our model to (a) scale more efficiently with increasing atom count while taking (b) larger steps with (c) lower error remains an open challenge.
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Congrats @AlexanderTong7! Also, if you are a recent CS/Math/Physics graduate: we are hiring PhD students. Deadline is 1st of Nov phd.aithyra.at/
Happy to announce I've been named a 2026 #AI2050 Early Career Fellow by @SchmidtSciences. I’ll investigate generative models for molecules as part of a global cohort working to ensure AI benefits society by 2050.
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Congrats to @zwblasingame and @sgmccallum - Strong Stochastic Flow Maps has been accepted to #NeurIPS2026 as an Oral! We're looking forward to share more results on applications and improvements of these models soon.
Introducing Strong Stochastic Flow Maps TLDR: Stochastic Flow Maps where we learn the stochastic solution path. Work led by Sam McCallum, @zwblasingame, with Timothy Herschelll, @AlexanderTong7, and @JamesFosterBath Arxiv: arxiv.org/pdf/2606.01086 Code: github.com/sammccallum/ssfm
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We're recruiting PhD students at #AITHYRA in Vienna this fall! Join us to work on basic ML problems motivated by open challenges in the life sciences. Details & apply: phd.aithyra.at
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Niklas Rindtorff retweeted
Met a German founder this week and asked him if all the stories one reads about the challenges of startups in Germany are exaggerated. "No, they're understated." Proceeded to describe spending a full day having a 90-page investment contract read to him (mandatory under German law; § 13 BeurkG) by a notary that then charged €30,000. That was for his first company. His second company, needless to say, was not incorporated in Germany.
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An announcement: Under the leadership of Mario Draghi and @patrickc we have set up the Rhine Group: policymakers, economists, entrepreneurs and business people pushing European reforms and the Draghi agenda. rhinegroup.eu/
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Niklas Rindtorff retweeted
Surreal endnotes section to have in an official government report – at Mount Rainier, MD
In response to @POTUS's call for a revival of America's scientific enterprise, today I’m releasing Science: A New Golden Age. This report is a blueprint for renewing American scientific leadership for the 21st century.
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Niklas Rindtorff retweeted
💠Introducing Clari, a generative model to predict organic crystal structure in seconds. Clari’s speed makes it feasible to do virtual screening of organic molecules on the basis of solid-state properties. co-first with Alston Lo @alston1o and Luka Mucko @srboljubbosanac
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Niklas Rindtorff retweeted
maaaaan
Replying to @claudeai
Fable 5’s safeguards detect requests related to cybersecurity, biology and chemistry, and distillation. Users are informed whenever a fallback occurs—on average in less than 5% of sessions. We’ll keep refining the safeguards to reduce false positives.
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