2021.6.28 Neural papers

06-23-2021	Evolving Hierarchical Memory-Prediction Machines in Multi-Task Reinforcement Learning by Stephen Kelly et al
06-23-2021	Alias-Free Generative Adversarial Networks by Tero Karras et al
06-25-2021	Learning Gradual Argumentation Frameworks using Genetic Algorithms by Jonathan Spieler et al
06-22-2021	A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimization by Jinjin Xu et al
06-22-2021	Randomness In Neural Network Training: Characterizing The Impact of Tooling by Donglin Zhuang et al
06-23-2021	Should You Go Deeper? Optimizing Convolutional Neural Network Architectures without Training by Receptive Field Analysis by Mats L. Richter et al
06-25-2021	A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation by M Ganesh Kumar et al
06-22-2021	Recurrent Neural Network from Adders Perspective: Carry-lookahead RNN by Haowei Jiang et al
06-23-2021	Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis by Xiaofeng Liu et al
06-22-2021	Online Ordering Platform City Distribution Based on Genetic Algorithm by Yu Du
06-22-2021	Towards Biologically Plausible Convolutional Networks by Roman Pogodin et al
06-23-2021	Prospects for Analog Circuits in Deep Networks by Shih-Chii Liu et al