1 citations · 1 across the 1 of their papers we have counts for
2 papers
cond-mat.stat-mech2026★ 1 cited
Dreaming up scale invariance via inverse renormalization group
Adam Rançon, Ulysse Rançon, Tomislav Ivek +1
We explore how minimal neural networks can invert the renormalization group (RG) coarse-graining procedure in the two-dimensional Ising model, effectively ``dreaming up'' microscop…
cs.NE2025
DelRec: learning delays in recurrent spiking neural networks
Alexandre Queant, Ulysse Rançon, Benoit R Cottereau +1
Spiking neural networks (SNNs) are a bio-inspired alternative to conventional real-valued deep learning models, with the potential for substantially higher energy efficiency. Inter…