Reproducible Research

At BENS we support Reproducible Research (opens in a new window) for our publications. Here we make support material available for our publications. Currently, we have this available for the following papers:

OPIUM: J. Tapson and A. van Schaik, "Learning the pseudoinverse solution to network weights," Neural networks, vol. 45, pp. 94–100, September 2013.

Fast Learning: L. Kuhlmann, M. Hauser-Raspe, J. H. Manton, D. B. Grayden, J. Tapson, and A. van Schaik, "Approximate, computationally efficient online learning in bayesian spiking neurons," Neural computation, vol. 26, no. 3, pp. 472–96, March 2014.

SKAN: S. Afshar, L. George, J. Tapson, A. van Schaik, and T. J. Hamilton, "Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels," Frontiers in Neuroscience, vol. 8, pp. 1–18, November 2014.

Dynamic OPIUM: A. van Schaik and J.Tapson, " Online and adaptive pseudoinverse solutions for ELM weights," Neurocomputing, vol. 149, pp. 233-238, June 2015

Bayesian Decoding: Patrick Kasi, James Wright, Heba Khamis, Ingvars Birznieks, André van Schaik, "The Bayesian Decoding of Force Stimuli from Slowly Adapting Type I Fibers in Humans", PLOS One, 2016.

EMNIST: an extension of MNIST to handwritten letters; Gregory Cohen, Saeed Afshar, Jonathan Tapson, and André van Schaik; arXiv ID:1702.05373, 2017

ATIS Planes: The ATIS Planes dataset is an event-based of free hand dropped airplane models; Saeed Afshar, Tara Julia Hamilton Jonathan Tapson, André van Schaik, and Gregory Cohen; arXiv ID:1603.04223