1 citations · 1 across the 2 of their papers we have counts for
2 papers
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…
cs.LG2024
Exploring the limits of Hierarchical World Models in Reinforcement Learning
Robin Schiewer, Anand Subramoney, Laurenz Wiskott
Hierarchical model-based reinforcement learning (HMBRL) aims to combine the benefits of better sample efficiency of model based reinforcement learning (MBRL) with the abstraction c…