2019.09.08 Neural papers

09-05-2019	Additive function approximation in the brain by Kameron Decker Harris
09-04-2019	Distance transform regression for spatially-aware deep semantic segmentation by Nicolas Audebert et al
09-06-2019	DRLViz: Understanding Decisions and Memory in Deep Reinforcement Learning by Theo Jaunet et al
09-04-2019	Learning sparse representations in reinforcement learning by Jacob Rafati et al
09-04-2019	Deep Convolutional Networks in System Identification by Carl Andersson et al
09-05-2019	TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs by Houssem Ben Braiek et al
09-05-2019	Minibatch Processing in Spiking Neural Networks by Daniel J. Saunders et al
09-05-2019	Port-Hamiltonian Approach to Neural Network Training by Stefano Massaroli et al
09-04-2019	Reservoir Computing based on Quenched Chaos by Jaesung Choi et al
09-04-2019	A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks by Andrés Camero et al
09-03-2019	An efficient and perceptually motivated auditory neural encoding and decoding algorithm for spiking neural networks by Zihan Pan et al