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Synthesising photo realistic images using GANs (SPADE Method). For more details refer to the original paper presented in CVPR 2019: https://arxiv.org/abs/1903.07291
Explaining the Explainer: A First Theoretical Analysis of LIME
Damien Garreau, Ulrike von Luxburg : https://arxiv.org/abs/2001.03447
#ArtificialIntelligence #DeepLearning #MachineLearning
Can an #AI deep neural network be trained to diagnose low blood sugar from the ECG signal?
https://go.nature.com/2NrqzxM

Fingerpicks are never pleasant and in some circumstances are particularly cumbersome. Taking fingerpick during the night certainly is unpleasant, especially for patients in paediatric age.

"Our innovation consisted in using artificial intelligence for automatic detecting hypoglycaemia via few ECG beats. This is relevant because ECG can be detected in any circumstance, including sleeping."
https://m.medicalxpress.com/news/2020-01-ai-glucose-ecg-fingerprick.html
Choosing the Sample with Lowest Loss makes SGD Robust

https://arxiv.org/abs/2001.03316
Deep Plastic Surgery: Robust and Controllable Image Editing with Human-Drawn Sketches
Yang et al.: https://arxiv.org/abs/2001.02890
#ArtificialIntelligence #DeepLearning #MachineLearning
Deep Residual Dense U-Net for Resolution Enhancement in Accelerated MRI Acquisition. https://arxiv.org/abs/2001.04488
Symmetric Skip Connection Wasserstein GAN for High-Resolution Facial Image Inpainting. https://arxiv.org/abs/2001.03725
Can Giraffes Become Birds? An Evaluation of Image-to-image Translation for Data Generation. https://arxiv.org/abs/2001.03637
Backward Feature Correction: How Deep Learning Performs Deep Learning
https://arxiv.org/abs/2001.04413