remember when ensembles were the cool word before they got erased from collective consciousness and replaced with deep things? it can't even be a decade, was it 2012 or something?
If you train an ensemble of models with random dropout, you have an ensemble. Models trained with dropout will still have significant variation from run to run.
It's a common interpretation: https://arxiv.org/abs/1706.06859
In particular, this paper neglected to do the obvious thing: ensemble networks trained with dropout. It improves performance over dropout alone.