3 papers
cs.IT2026
Sample complexity bounds for the Jensen-Shannon divergence
Oren Richter, Adi Ben-Ari, Tom Talpir +1
The Jensen-Shannon divergence (JSD) is a symmetric and bounded measure of the dissimilarity of two probability distributions, which has become a standard tool in statistics, inform…
q-bio.NC2026
Identifying structural design principles shaping the computational abilities of recurrent neural networks
Tom Talpir, Elad Schneidman
Understanding how the architecture of neural networks shapes the computations they carry is a central challenge in neuroscience and machine learning. While specific circuit archite…
q-bio.NC2025
Semantic representations emerge in biologically inspired ensembles of cross-supervising neural networks
Roy Urbach, Elad Schneidman
Brains learn to represent information from a large set of stimuli, typically by weak supervision. Unsupervised learning is therefore a natural approach for exploring the design of…