2020.9.28 Neural papers

09-23-2020	Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves by Luke Metz et al
09-22-2020	Tensor Programs III: Neural Matrix Laws by Greg Yang
09-23-2020	Neurocoder: Learning General-Purpose Computation Using Stored Neural Programs by Hung Le et al
09-23-2020	Adversarial robustness via stochastic regularization of neural activation sensitivity by Gil Fidel et al
09-23-2020	Parameters for the best convergence of an optimization algorithm On-The-Fly by Valdimir Pieter
09-24-2020	EPNE: Evolutionary Pattern Preserving Network Embedding by Junshan Wang et al
09-23-2020	Procrustes: a Dataflow and Accelerator for Sparse Deep Neural Network Training by Dingqing Yang et al
09-24-2020	A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder by Youngkyu Kim et al
09-23-2020	Deep Learning of Individual Aesthetics by Jon McCormack et al
09-23-2020	Evolution, Symbiosis, and Autopoiesis in the Game of Life by Peter D. Turney
09-23-2020	An electronic neuromorphic system for real-time detection of High Frequency Oscillations (HFOs) in intracranial EEG by Mohammadali Sharifhazileh et al
09-22-2020	Complex Vehicle Routing with Memory Augmented Neural Networks by Marijn van Knippenberg et al
09-22-2020	Multi-threaded Memory Efficient Crossover in C++ for Generational Genetic Programming by W. B. Langdon