Peng Yan

Nature Electronics · 2018–2019

A researcher in the Science corpus: 4 papers; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Peng Yan's perspective

Ordered by how strongly the researchers Peng Yan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
5. Learning to Forget: Continual Prediction with LSTM
6. Nonlinear dimensionality reduction by locally linear embedding.
7. Generalization of backpropagation with application to a recurrent gas market model
8. A Focused Backpropagation Algorithm for Temporal Pattern Recognition
9. A Theoretical Framework for Back-Propagation
10. Training deep neural networks with low precision multiplications

Their papers

• Fully memristive neural networks for pattern classification with unsupervised learning (2018) — 993 citations
• Reinforcement learning with analogue memristor arrays (2019) — 334 citations
• Efficient and self-adaptive in-situ learning in multilayer memristor neural networks (2018) — 828 citations
• Long short-term memory networks in memristor crossbar arrays (2018) — 368 citations