Machine Learning at the Limit
Alex ColagrandeIl mio Substack personale
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 12 | Founded | 5 months ago | Last Issue | 20 days ago |
| Active | |||||
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machinelearningatthelimit.substack....Latest Issues
12. NeuralDEM: Real-time Simulation of Industrial Particulate Flows
NeuralDEM presents an end-to-end approach to replace discrete element method (DEM) routines. Image taken from [1].
Introduction
While most deep learning models for physics simulations are still just tested on academic benchmarks, we dis...
11. Universal Physics Transformer (UPT)
Introduction
In the last blog post we discussed about Aurora, the first foundation model for the atmosphere. Among the authors figures Johannes Brandstetter, that after his experience at Microsoft, came back to Austria with a faculty pos...
10. Aurora: A Foundation model of the atmosphere
Introduction
Back in 2024, it was already clear that large deep learning models trained on vast amounts of data (i.e., foundation models) exhibited impressive capabilities. By that time, models such as (Chat)GPT-4 for text, DALL·E 3 for...
9. A small review on Point Transformers
Image taken from [1]
Introduction
Often data comes as a collection of points sampled in space, this is often the case for 3D computer vision and numerical simulations. This collections of points are called point clouds and, due to their...
8. A small review on Point Networks
Just a point cloud. Image taken from a dataset in [2]
Introduction
In most areas of machine learning, data are regularly sampled, such as images where pixels lie on a regular grid. However, when this assumption no longer holds, the prob...
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Authors
The writers behind this newsletter.
PhD student in ML4Physics at Paris Dauphine - PSL
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