Deep Learning Research Review: Generative Adversarial Nets

This edition of Deep Learning Research Review explains recent research papers in the deep learning subfield of Generative Adversarial Networks. Don’t have time to read some of the top papers? Get the overview here. By Adit Deshpande, UCLA. Starting this week, I’ll be doing a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week I’ll begin with Generative Adversarial Networks.  Introduction  According to Yann LeCun, “adversarial training is the coolest thing since sliced bread”. I’m inclined to believe so because I don’t think sliced bread ever created this much buzz and excitement within the deep learning community. In this post, we’ll be looking at 3 papers that built on the pioneering work of Ian Goodfellow in 2014. Quick…


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