2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Emergence of Fibrations, Compression, and Symmetry Breaking in Artificial Neural Networks
Osvaldo M Velarde, Lucas C Parra, Alireza Hashemi +1
Artificial neural networks are often regarded as powerful yet opaque black boxes. Here, we demonstrate that learning in deep neural networks generates local symmetries known in gra…
cs.NE2024★ 2 cited
Recurrent Joint Embedding Predictive Architecture with Recurrent Forward Propagation Learning
Osvaldo M Velarde, Lucas C Parra
Conventional computer vision models rely on very deep, feedforward networks processing whole images and trained offline with extensive labeled data. In contrast, biological vision…
cs.LG2024★ 1 cited
The Role of Fibration Symmetries in Geometric Deep Learning
Osvaldo Velarde, Lucas Parra, Paolo Boldi +1
Geometric Deep Learning (GDL) unifies a broad class of machine learning techniques from the perspectives of symmetries, offering a framework for introducing problem-specific induct…