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Digital Twin Enabled Smart Control Engineering as an Industrial AI: A New Framework and A Case Study. (arXiv:2007.03677v1 [eess.SP]) arxiv.org/abs/2007.03677

DRIVE: A Digital Network Oracle for Cooperative Intelligent Transportation Systems. (arXiv:2007.03680v1 [cs.NI]) arxiv.org/abs/2007.03680

Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data. (arXiv:2007.03724v1 [cs.LG]) arxiv.org/abs/2007.03724

Predictive Analytics for Water Asset Management: Machine Learning and Survival Analysis. (arXiv:2007.03744v1 [eess.SP]) arxiv.org/abs/2007.03744

Electric Vehicle transition in the UK. (arXiv:2007.03745v1 [cs.CY]) arxiv.org/abs/2007.03745

Transfer Learning for Brain-Computer Interfaces: A Complete Pipeline. (arXiv:2007.03746v1 [eess.SP]) arxiv.org/abs/2007.03746

On Cokriging, Neural Networks, and Spatial Blind Source Separation for Multivariate Spatial Prediction. (arXiv:2007.03747v1 [eess.SP]) arxiv.org/abs/2007.03747

Surveying Off-Board and Extra-Vehicular Monitoring and Progress Towards Pervasive Diagnostics. (arXiv:2007.03759v1 [eess.AS]) arxiv.org/abs/2007.03759

Spatiotemporal Flexible Sparse Reconstruction for Rapid Dynamic Contrast-enhanced MRI. (arXiv:2007.02937v1 [physics.med-ph]) arxiv.org/abs/2007.02937

Consensus Multi-Agent Reinforcement Learning for Volt-VAR Control in Power Distribution Networks. (arXiv:2007.02991v1 [eess.SY]) arxiv.org/abs/2007.02991

Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters. (arXiv:2007.03001v1 [eess.AS]) arxiv.org/abs/2007.03001

Optimal Dynamic Mechanism Design with Stochastic Supply and Flexible Consumers. (arXiv:2007.03007v1 [cs.GT]) arxiv.org/abs/2007.03007

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems. (arXiv:2007.03025v1 [eess.SY]) arxiv.org/abs/2007.03025

PHELP: Pixel Heating Experiment Learning Platform for Education and Research on IAI-based Smart Control Engineering. (arXiv:2007.03048v1 [eess.SY]) arxiv.org/abs/2007.03048

Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models. (arXiv:2007.03051v1 [cs.CY]) arxiv.org/abs/2007.03051

Benefitting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution. (arXiv:2007.03053v1 [eess.IV]) arxiv.org/abs/2007.03053

Revealing the limits of single-particle imaging with orientation disconcurrence. (arXiv:2007.03054v1 [physics.data-an]) arxiv.org/abs/2007.03054

Deep Learning Models for Visual Inspection on Automotive Assembling Line. (arXiv:2007.01857v1 [cs.CV]) arxiv.org/abs/2007.01857

Selecting Regions of Interest in Large Multi-Scale Images for Cancer Pathology. (arXiv:2007.01866v1 [eess.IV]) arxiv.org/abs/2007.01866

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