44 citations · 157 across the 31 of their papers we have counts for
34 papers
A Phenomenology of Neural Geometry in Vision-Language-Action Models
Mozes Jacobs, Aiden Swann, Mathilde Papillon +16
Robotic manipulation is inherently geometric, but what shape does the world take inside the policy that performs it? Prior work on vision-language-action (VLA) policies establishes…
When Models Don't Manipulate Manifolds: The Geometry of a Comparison Task
Sai Sumedh R. Hindupur, Hadas Orgad, Thomas Fel +1
One of the current premises of mechanistic interpretability research is that detailed accounts of the geometry of neural network representations can tell us how models perform comp…
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models
Alexander Lin, Bahareh Tolooshams, Yves Atchadé +1
Latent Gaussian models have a rich history in statistics and machine learning, with applications ranging from factor analysis to compressed sensing to time series analysis. The cla…
Learning Linear Groups in Neural Networks
Emmanouil Theodosis, Karim Helwani, Demba Ba
Employing equivariance in neural networks leads to greater parameter efficiency and improved generalization performance through the encoding of domain knowledge in the architecture…
Sparse, Geometric Autoencoder Models of V1
Jonathan Huml, Abiy Tasissa, Demba Ba
The classical sparse coding model represents visual stimuli as a linear combination of a handful of learned basis functions that are Gabor-like when trained on natural image data.…
SHAPER: Can You Hear the Shape of a Jet?
Demba Ba, Akshunna S. Dogra, Rikab Gambhir +2
The identification of interesting substructures within jets is an important tool for searching for new physics and probing the Standard Model at colliders. Many of these substructu…