Quan.Z Sheng
Artificial Intelligence · with Alhazmi · 2019
A researcher in the Science corpus: 2 papers; trusts 245 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 123 citations into it
- Natural Language Processing — 84 citations into it
- Computer Vision and Pattern Recognition — 43 citations into it
- Safety, Robustness & Interpretability — 38 citations into it
- Signal Processing — 26 citations into it
- Evaluation & Benchmarks — 15 citations into it
- Computer Networks and Communications — 7 citations into it
- Optimization & Training — 5 citations into it
Whom Quan.Z Sheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Yann LeCun
- Ian J. Goodfellow
- Kaiming He
- Oriol Vinyals
- Alex Graves
Who trusts Quan.Z Sheng overall
Papers from Quan.Z Sheng's perspective
Ordered by how strongly the researchers Quan.Z Sheng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting (2019) — 308 citations
- Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey (2019) — 601 citations