Manuel Lecha
@manuellecha.bsky.social
ELLIS PhD Student (IIT & Oxford) | Mathematics & Computer Science | Geometric Deep Learning
Learning representations is learning the structure of data—and structure is geometry.
📢The second edition of ✨GRaM workshop✨ is here this time at #ICLR26.
🌟Submit your exciting works in Geometry-grounded representations.
We welcome submissions in multiple tracks i.e.
📄 Proceedings
📝extended abstract
👩🏫Tutorial/blogpost
as well as an exciting challenge!
🌟Submit your exciting works in Geometry-grounded representations.
We welcome submissions in multiple tracks i.e.
📄 Proceedings
📝extended abstract
👩🏫Tutorial/blogpost
as well as an exciting challenge!
December 18, 2025 at 9:24 AM
Learning representations is learning the structure of data—and structure is geometry.
Reposted by Manuel Lecha
🧵 1/7
Our new preprint “Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding" is online at arxiv.org/abs/2505.17939
An amazing project with a dream team, which led to a principled Topological Deep Learning architecture for a unique real-world use case!
Our new preprint “Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding" is online at arxiv.org/abs/2505.17939
An amazing project with a dream team, which led to a principled Topological Deep Learning architecture for a unique real-world use case!
May 28, 2025 at 2:56 PM
🧵 1/7
Our new preprint “Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding" is online at arxiv.org/abs/2505.17939
An amazing project with a dream team, which led to a principled Topological Deep Learning architecture for a unique real-world use case!
Our new preprint “Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding" is online at arxiv.org/abs/2505.17939
An amazing project with a dream team, which led to a principled Topological Deep Learning architecture for a unique real-world use case!