terryum/awesome-deep-learning-papers

Organizes 100 seminal deep learning papers (2012-2016) by research domain—including CNNs, NLP, reinforcement learning, and generative models—using citation thresholds that scale by publication year to identify foundational work. Provides downloadable paper corpus with accompanying utilities for bibliography generation and author network analysis. Emphasizes broadly applicable theoretical contributions over application-specific papers, filtering for cross-domain impact rather than citation count alone.

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