Learning to remember: Dynamic Generative Memory for Continual Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Continual Unsupervised Representation Learning (2019, methodology): “Another popular approach is that of rehearsal-based methods (Robins, 1995), where the data distribution from earlier tasks is captured by samples from a generative model trained concurrently (Shin et al., 2017; van de Ven & Tolias, 2018; Ostapenko et al., 2018).”