An intuitive introduction to Jacobi fields and their applications in machine learning on Riemannian manifolds.

A large driver of the complexity of graph learning is the interplay between structure and features. When analyzing the expressivity of graph neural networks, however, existing approaches ignore featur...

YouTube video by Bastian Grossenbacher-Rieck

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It’s not just you. Survey says: “Twitter sucks now and all the cool kids are moving to Bluesky”…

TopoBench: A comprehensive benchmarking framework for Topological Deep Learning models and datasets.

TopoBench is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning - geometric-intelligence/TopoBench

We initiate an open-source library for the efficient analysis of temporal graphs. We consider one of the standard models of dynamic networks in which each edge has a discrete timestamp and transition ...

An exploration of N-dimensional rotary positional embeddings (RoPE) for vision transformers.

A NeurIPS-endorsed conference in Europe held in Copenhagen, Denmark

We give a deterministic $O(m\log^{2/3}n)$-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition model. This is the fi...