Storage capacity of spatio-temporal patterns in LIF spiking networks: mixed rate and phase coding Antonio de Candia and Siliva Scarpetta,

Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks Bodo Rueckauer, Iulia-Alexandra Lungu, Yuhuang Hu, and Michael Pfeiffer

Somatic inhibition controls dendritic selectivity in a 2 sparse coding network of spiking neurons. Damien Drix

Fast and Efficient Asynchronous Neural Computation in Deep Adaptive Spiking Neural Networks Davide Zambrano and Sander Bohte

Spiking memristor logic gates are a type of time-variant perceptron. Ella Gale. 

A wake-sleep algorithm for recurrent, spiking neural networks Johannes Thiele, Peter Diehl and Matthew Cook

Deep counter networks for asynchronous event-based processing Jonathan Binas, Giacomo Indiveri and Michael Pfeiffer

Spike-based reinforcement learning for temporal stimulus segmentation and decision making Luisa Le Donne, Luca Mazzucato, Robert Urbanczik, Walter Senn and Giancarlo La Camera

Deep Spiking Networks Peter O’Connor and Max Welling 

Working Memory in Adaptive Spiking Neural Networks Roeland Nusselder, Davide Zambrano and Sander Bohte

An Efficient Approach to Boosting Performance of Deep Spiking Network Training Seongsik Park, Sung-gil Lee, Huynha Nam and Sungroh Yoon. 

Optimization-based computation with spiking neurons Stephen Verzi, Craig Vineyard, Eric Vugrin, Meghan Galiardi, Conrad James and James Aimone

Learning binary or real-valued time-series via spike-timing dependent plasticity  Takayuki Osogami 

Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity Thomas Mesnard, Wulfram Gerstner and Johanni Brea

Can we be formal in assessing the strengths and weaknesses of neural architectures? A case study using a spiking cross-correlation algorithm William Severa, Kristofor Carlson, Ojas Parekh, Craig Vineyard and James Aimone

Nonnegative autoencoder with simplified random neural network Yonghua Yin and Erol Gelenbe