2 papers
cs.LG2025
How does training shape the Riemannian geometry of neural network representations?
Jacob A. Zavatone-Veth, Sheng Yang, Julian A. Rubinfien +1
In machine learning, there is a long history of trying to build neural networks that can learn from fewer example data by baking in strong geometric priors. However, it is not alwa…
cs.LG2024
The Numerical Stability of Hyperbolic Representation Learning
Gal Mishne, Zhengchao Wan, Yusu Wang +1
Given the exponential growth of the volume of the ball w.r.t. its radius, the hyperbolic space is capable of embedding trees with arbitrarily small distortion and hence has receive…