Generalizability theory

Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks

A survey of inverse reinforcement learning: Challenges, methods and progress

Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation

Task Agnostic Meta-Learning for Few-Shot Learning

Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques

From bulk effective mass to 2D carrier mobility accurate prediction via adversarial transfer learning

A comprehensive review of machine learning for superalloys: from data-driven prediction to intelligent design