41 citations · 42 across the 6 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.LG2026★ 1 cited
Training event-based neural networks with exact gradients via Differentiable ODE Solving in JAX
Lukas König, Manuel Kuhn, David Kappel +1
Existing frameworks for gradient-based training of spiking neural networks face a trade-off: discrete-time methods using surrogate gradients support arbitrary neuron models but int…
cond-mat.quant-gas2026
Diffusion in quantum state preparation: From passive cooling to system-bath engineering
Tim Pokart, Lukas König, Sebastian Diehl +1
We investigate and compare two particle number-conserving protocols for the preparation of a topologically nontrivial state. The first is derived from thermally coupling the system…