3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians
Rainer Engelken
Training recurrent neural networks (RNNs) remains a challenge due to the instability of gradients across long time horizons, which can lead to exploding and vanishing gradients. Re…
q-bio.NC2023★ 3 cited
SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks
Rainer Engelken
Spiking Neural Networks (SNNs) are biologically-inspired models that are capable of processing information in streams of action potentials. However, simulating and training SNNs is…