50 citations · 100 across the 3 of their papers we have counts for
4 papers
DelRec: learning delays in recurrent spiking neural networks
Alexandre Queant, Ulysse Rançon, Benoit R Cottereau +1
Biological neurons transmit information with stereotyped electrical impulses called ``spikes'', sensitive to coincident timings. Spiking Neural Networks (SNNs), introduced in the n…
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…
Optical flow estimation from event-based cameras and spiking neural networks
Javier Cuadrado, Ulysse Rançon, Benoît Cottereau +2
Event-based cameras are raising interest within the computer vision community. These sensors operate with asynchronous pixels, emitting events, or "spikes", when the luminance chan…
StereoSpike: Depth Learning with a Spiking Neural Network
Ulysse Rançon, Javier Cuadrado-Anibarro, Benoit R. Cottereau +1
Depth estimation is an important computer vision task, useful in particular for navigation in autonomous vehicles, or for object manipulation in robotics. Here we solved it using a…