2021.11.1 Neural papers

10-26-2021	Precise URL Phishing Detection Using Neural Networks by Aman Rangapur et al
10-26-2021	MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge by Geng Yuan et al
10-26-2021	Biological learning in key-value memory networks by Danil Tyulmankov et al
10-26-2021	Bootstrapping Concept Formation in Small Neural Networks by Minija Tamosiunaite et al
10-26-2021	Brain-inspired feature exaggeration in generative replay for continual learning by Jack Millichamp et al
10-26-2021	An improved multiobjective evolutionary algorithm based on decomposition and adaptive multi-reference points by Wang Chen et al
10-27-2021	Learning where to learn: Gradient sparsity in meta and continual learning by Johannes von Oswald et al
10-28-2021	Location-routing Optimisation for Urban Logistics Using Mobile Parcel Locker Based on Hybrid Q-Learning Algorithm by Yubin Liu et al
10-27-2021	Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons by Paul Haider et al
10-26-2021	Automated Support for Unit Test Generation: A Tutorial Book Chapter by Afonso Fontes et al
10-26-2021	BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks by Guangzhi Tang et al
10-27-2021	A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection by Xubin Wang et al
10-26-2021	Research on the inverse kinematics prediction of a soft actuator via BP neural network by Huichen Ma et al
10-27-2021	Comprehensive learning particle swarm optimization enabled modeling framework for multi-step-ahead influenza prediction by Siyue Yang et al