Deep learning without contrastive divergence

Can somebody recommend me some recent deep learning papers without using contrastive divergence learning rule?

If I understand correctly the essence of deep learning is the unsupervised pre-training of multi-layer network, and it should not be restricted to using only contrastive divergence learning rules. However, I haven't found any deep learning papers without contrastive divergence. I am new in this field.