Seems that deep learning can benefit from gradient boosting too (at least, from a computational perspective).

https://arxiv.org/abs/1706.04964 "Learning Deep ResNet Blocks Sequentially using Boosting Theory"

(As for the lay-man description: I thought boosting performed better out-of-the-box on dense data than on sparse data, because most feature sub-selections for bagging are on zero'd features)