Sebastian Schmon @SeBayesian

Machine Learning @Latent_Labs, anything from classical statistics to modern machine learning and generative AI, previous @altos_labs schmons.github.io United Kingdom Joined June 2020

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Latent Labs @Latent_Labs

a month ago

Showcasing Latent-X's breakthrough macrocycle designs. Our AI achieved an unprecedented 91-100% hit rate with single-digit micromolar binding affinities—functional binders on every single target tested. Explore our binders without logging in: platform.latentlabs.com

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Simon Kohl @saakohl

2 months ago

It's been a fantastic first few days of public usage of the Latent Platform! The team has been providing white glove user support - for feedback or requests, you can reach us through our feedback channels: form.typeform.com/to/P4vxcyT2?ty… Also, check out our sharing feature below: You…

Latent Labs @Latent_Labs

2 months ago

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Latent Labs @Latent_Labs

2 months ago

🧬 Latent-X is our first frontier model for protein design. For mini-binders, our AI model achieved picomolar binding affinities — the strongest reported vs prior methods in head-to-head lab validation. Explore our best binders here (no login required): platform.latentlabs.com…

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Sebastian Schmon @SeBayesian

2 months ago

I'm really excited about what we build here, the machine learning, the science, but also the platform! Proud to be part of an amazing team!

Simon Kohl @saakohl

2 months ago

I'm really excited about what we build here, the machine learning, the science, but also the platform! Proud to be part of an amazing team!

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Simon Kohl @saakohl

2 months ago

Introducing Latent-X — our all-atom frontier AI model for protein binder design. State-of-the-art lab performance, widely accessible via the Latent Labs Platform. Free tier: platform.latentlabs.com Blog: latentlabs.com/latent-x/ Technical report: tinyurl.com/latent-X

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Simon Kohl @saakohl

7 months ago

@Latent_Labs comes out of stealth today with $50M funding. Our goal? To push the frontiers of generative biology, giving partners instant access to tools capable of accelerating drug design. Every biotech or pharma company searching for the best therapeutic molecules understands…

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Sebastian Schmon @SeBayesian

7 months ago

Or: "Why are Chatbots trained to tell us what we want to hear so reluctant to say 'I don't know'?" It's a mystery. 🤔

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Sebastian Schmon @SeBayesian

9 months ago

If you believe (=0) do you also believe (sinx)/n = six? In maths you can't just leave out the definitions and start with the proof. Do you mean both x to be exactly the same entity or do you mean one fixed but unknown quantity for every letter in the alphabet, i.e. (x'-x)?

Anthony Bonato @Anthony_Bonato

9 months ago

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Bastian Grossenbacher-Rieck @Pseudomanifold

10 months ago

📢 Exciting News! Our paper, “Bayesian Computation Meets Topology,” has just been published in TMLR! 🎉 👉openreview.net/forum?id=0h1Dt… 👈 Here’s a deep dive into how #topology and #bayes(ian) computation come together to enhance parameter inference: 📌 Why Topology? Topology…

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Joel Dyer @JoelNMDyer

10 months ago

This Friday at #ICAIF 2024, together with @NickBishop5 and #AniCalinescu, we'll give a tutorial on building and calibrating differentiable agent-based models of financial systems! Notebooks and materials are freely available on our tutorial website: largeagentcollider.github.io/icaif_tutorial/

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Crémieux @cremieuxrecueil

11 months ago

Today's a good reminder of how much further in the future we could be living if regulators simply got out of the way.

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Sebastian Schmon @SeBayesian

12 months ago

Question: if a neurips paper decision is out, but you don't know the result yet, is the decision a random variable or not? 🤔

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Sebastian Schmon @SeBayesian

a year ago

The question at this point is: what is the environmental impact of an environmental impact statement?

YIMBYLAND @YIMBYLAND

a year ago

The question at this point is: what is the environmental impact of an environmental impact statement?

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Stat.ML Papers @StatMLPapers

a year ago

PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis ift.tt/BRf4Mxv

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Sebastian Schmon @SeBayesian

a year ago

"Moving to computational medicine will require being comfortable with understanding biology by outcomes rather than by mechanisms." That's an interesting and controversial take. I don't think this is true, but I wonder what @DavidDeutschOxf would say about this 🙂

Patrick Schwab @schwabpa

a year ago

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Sebastian Schmon @SeBayesian

a year ago

Excited to share that our paper on "Approximate Bayesian Computation with Path Signatures" has been recognized with the outstanding paper award at @UncertaintyInAI! Grateful for my amazing collaborators @JoelNMDyer @pw_cannon

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Joel Dyer @JoelNMDyer

a year ago

Next week I’ll be @UncertaintyInAI #UAI2024 & @aabi_org #AABI2024 in Vienna to present my Spotlight paper w/ @pw_cannon & @SeBayesian on approx. Bayesian inference for time series simulators using path signatures: openreview.net/forum?id=MsU6s…. Come chat about simulators & #Bayes!

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Sebastian Schmon @SeBayesian

a year ago

I'm sure whoever came up with the High-School track idea at #neurips meant we'll, but people should really consider the incentives they create. This was 100% the guaranteed outcome of this.

Alexander Terenin @avt_im

a year ago

I'm sure whoever came up with the High-School track idea at #neurips meant we'll, but people should really consider the incentives they create. This was 100% the guaranteed outcome of this.