PixelCNN is a deep learning architecture - or bundle of architectures - designed to generate highly realistic-looking images. To use it, no reverse-engineering of arXiv papers or search for reference implementations is required: TensorFlow Probability ... [Read more...]

Compared to other applications, deep learning models might not seem too likely as victims of privacy attacks. However, methods exist to determine whether an entity was used in the training set (an adversarial attack called member inference), and techni... [Read more...]

Deep learning need not be irreconcilable with privacy protection. Federated learning enables on-device, distributed model training; encryption keeps model and gradient updates private; differential privacy prevents the training data from leaking. As of... [Read more...]