Yisheng Lv

Building and Construction · 2015–2021

A researcher in the Science corpus: 6 papers; trusts 18 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Building and Construction — 46 citations into it; #326 of 2,909 by trust here, #190 by citations
• Transportation — 38 citations into it; #424 of 2,062 by trust here, #95 by citations
• Artificial Intelligence — 29 citations into it
• Control and Systems Engineering — 25 citations into it; #1,633 of 8,257 by trust here, #348 by citations
• Computer Vision and Pattern Recognition — 19 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Model Architectures — 8 citations into it

Whom Yisheng Lv trusts overall

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

1. Billy M. Williams
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Graves
5. Richard S. Sutton
6. Sepp Hochreiter
7. J. Urgen Schmidhuber
8. Hussein Dia
9. Ilya Sutskever
10. Eleni I. Vlahogianni

Who trusts Yisheng Lv overall

1. Daniel Hsu
2. Zhiyong Cui
3. Cathy Wu
4. John Cristian Borges Gamboa
5. Ruimin Ke
6. Haitao Yuan
7. Min-Joo Kang
8. Yongxue Tian
9. Yinhai Wang
10. Senzhang Wang

Papers from Yisheng Lv's perspective

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

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

Their papers

• Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting (2021) — 339 citations
• Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management (2020) — 299 citations
• An efficient realization of deep learning for traffic data imputation (2016) — 313 citations
• Travel time prediction with LSTM neural network (2016) — 331 citations
• Traffic signal timing via deep reinforcement learning (2016) — 540 citations
• Traffic Flow Prediction With Big Data: A Deep Learning Approach (2015) — 2,921 citations