In this talk, we discuss recent advances in machine learning, namely, continual learning and adversarial learning. The problem of learning with an adversarial will be formalized and we present new approaches that improve the robustness of neural networks and how to use explainability to detect adversarial samples.

**Speaker will be in-person**