Search Results for author: Roeland Nusselder

Found 3 papers, 1 papers with code

Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization

3 code implementations NeurIPS 2019 Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, Kwang-Ting Cheng, Roeland Nusselder

Together, the redefinition of latent weights as inertia and the introduction of Bop enable a better understanding of BNN optimization and open up the way for further improvements in training methodologies for BNNs.

Gating out sensory noise in a spike-based Long Short-Term Memory network

no code implementations ICLR 2018 Davide Zambrano, Isabella Pozzi, Roeland Nusselder, Sander Bohte

These adaptive spiking neurons implement an adaptive form of sigma-delta coding to convert internally computed analog activation values to spike-trains.

Efficient Computation in Adaptive Artificial Spiking Neural Networks

no code implementations13 Oct 2017 Davide Zambrano, Roeland Nusselder, H. Steven Scholte, Sander Bohte

Adaptive spike-time coding additionally allows for the dynamic control of neural coding precision: we show how a simple model of arousal in AdSNNs further halves the average required firing rate and this notion naturally extends to other forms of attention.

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