Quan Gan
Artificial Intelligence · with Zhang · 2019–2020
A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 86 citations into it
- Graph Learning — 58 citations into it
- Natural Language Processing — 23 citations into it
- Model Architectures — 22 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
Whom Quan Gan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Richard Socher
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Alex Graves
- Yann LeCun
- Kaiming He
- Jimmy Ba
Who trusts Quan Gan overall
Papers from Quan Gan's perspective
Ordered by how strongly the researchers Quan Gan trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs (2019) — 884 citations
- BP-Transformer: Modelling Long-Range Context via Binary Partitioning (2019) — 85 citations
- DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs (2020) — 334 citations
- Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks. (2019) — 1,357 citations