Yan Xu

Electrical and Electronic Engineering · IEEE Transactions on Smart Grid · 2015–2020

A researcher in the Science corpus: 6 papers; trusts 20 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 52 citations into it; #8,584 of 16,539 by trust here, #7,062 by citations
• Artificial Intelligence — 19 citations into it
• Control and Systems Engineering — 14 citations into it; #5,089 of 8,257 by trust here, #5,784 by citations
• Computer Vision and Pattern Recognition — 11 citations into it
• Model Architectures — 11 citations into it
• Natural Language Processing — 11 citations into it
• Reinforcement Learning — 5 citations into it

Whom Yan Xu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Pascal Vincent
2. Yoshua Bengio
3. Renzhi Lu
4. Alex Graves
5. Hilbert J. Kappen
6. Geoffrey E. Hinton
7. Ilya Sutskever
8. Hugo Larochelle
9. Paul J. Werbos
10. Diederik P. Kingma

Who trusts Yan Xu overall

1. Xin Chen

Papers from Yan Xu's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Short-Term Residential Load Forecasting Based on Resident Behaviour Learning (2018) — 517 citations
• Data-Driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method With Continuous Action Search (2019) — 307 citations
• A Multi-Agent Reinforcement Learning-Based Data-Driven Method for Home Energy Management (2020) — 354 citations
• Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network (2019) — 2,183 citations
• Multi-Stage Flexible Expansion Co-Planning Under Uncertainties in a Combined Electricity and Gas Market (2015) — 144 citations
• A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs (2018) — 413 citations