Who invented deep residual learning?
arXiv:2509.24732v1h-index: 1
Originality Synthesis-oriented
AI Analysis
This work addresses a historical question for AI researchers and practitioners, but it is incremental as it synthesizes existing knowledge without introducing new methods or data.
The paper investigates the origins of deep residual learning, a foundational concept in modern AI, by presenting a timeline of its evolution, but does not report any new experimental results or concrete numbers.
Modern AI is based on deep artificial neural networks (NNs). As of 2025, the most cited scientific article of the 21st century is an NN paper on deep residual learning with residual connections. Who invented this? We present a timeline of the evolution of deep residual learning.