58 citations · 71 across the 3 of their papers we have counts for
3 papers
Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent
Carlo Wenig, Raoul-Martin Memmesheimer, Christian Klos
The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for the extensively used leaky int…
Smooth Exact Gradient Descent Learning in Spiking Neural Networks
Christian Klos, Raoul-Martin Memmesheimer
Gradient descent prevails in artificial neural network training, but seems inept for spiking neural networks as small parameter changes can cause sudden, disruptive (dis-)appearanc…
Dynamical learning of dynamics
Christian Klos, Yaroslav Felipe Kalle Kossio, Sven Goedeke +2
The ability of humans and animals to quickly adapt to novel tasks is difficult to reconcile with the standard paradigm of learning by slow synaptic weight modification. Here we sho…