Sure.<p>Random forests are a very powerful machine learning method that has proven to give excellent performance with very little tuning.  Neural networks with many layers (aka deep learning) is the new frontier of machine learning - they are very powerful but require extensive tuning (the architecture of the network) and lots of examples before they become practical.<p>In this paper, the authors combine the two methods - they basically stack a random forest on top of a neural network, and obtain some cutting edge results.  One of the main theoretical results in the paper is that they propose a differentiable (which means you can use gradient-based optimization techniques) technique to optimize the parameters of the trees (which are the building blocks of the random forest).