🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

We are organizing a local NeurIPS in Cambridge this year on the 6th of Dec. If you are around, come listen and share your work. All relevant topics/departments welcome!

New article: "The geometry of data: the missing metric tensor and the Stein score" (blog.christianperone.com/2024/11/the-ge…). I show how you can derive a (efficient to compute) data manifold metric tensor with the Stein score alone ! Deep connections to diffusion, score-based models and physics.

A postdoc position is available in my group at Harvard Harvard SEAS to perform research at the intersection of Geometry & Machine Learning. Research interests include Representation Learning, Learning on Graphs & Manifolds, and applications in the Sciences. Details here:

Our new study shows that SARS-CoV-2 spike protein accumulates & persists in the body for years after infection, especially in the skull-meninges-brain axis, potentially driving long COVID. mRNA vaccines help but cannot stop it🔬🧠🦠🧵👇Cell Host & Microbe cell.com/cell-host-micr…

A few months ago Ilia Shumailov🦔 wrote a paper in nature "AI models collapse when trained on recursively generated data". We discussed this and other ML security research he did at University of Oxford - dropping on MLST in the next couple of days.

I'm looking for PhD applicants who have expertise in Gaussian processes and/or Transformers for an exciting PhD project If this sounds interesting, application deadline for funding is 3/12 Please share with people you think this might be relevant to! oatml.cs.ox.ac.uk/apply.html

overcoming scarcity with synthetic data

"Much of the point of a model like o1 is not to deploy it, but to generate training data for the next model. Every problem that an o1 solves is now a training data point for an o3." No, that won't work! Let me introduce you to something called Model Collapse. - Model Collapse

Fantastic talk from Zakhar Shumaylov at today's CIA seminar! 🚀 He shared insightful work on the Future of Synthetic Data, covering Model Collapse & Equivariant Neural Operators. 🔥 #AI #MachineLearning #SyntheticData

Hot take: I think we just demonstrated the first AI agent computer worm 🤔 When an agent sees a trigger image it's instructed to execute malicious code and then share the image on social media to trigger other users' agents This is a chance to talk about agent security 👇

If you are coming to #ICLR2025 come say hello. We will be presenting on how to turn Neural Operators equivariant even when all you know is the lie algebra! Generally happy to chat all things #geometry and #optimization in deep learning! 🔗arxiv.org/pdf/2410.02698

Imagine if, in the 1890s, Eastman Kodak had created an entire research team devoted to figuring out if film cameras actually did steal your soul.

4/26 at 3pm: 'Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups' Zakhar Shumaylov · Peter Zaika · James Rowbottom · Ferdia Sherry · Melanie Weber · Carola-Bibiane Schönlieb Submission: openreview.net/forum?id=7PLpi…

1/4) I am very happy to share our latest work on the information theory of generative diffusion: "Entropic Time Schedulers for Generative Diffusion Models" We find that the conditional entropy offers a natural data-dependent notion of time.