Jinchao Zhang
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 4 papers; trusts 201 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 97 citations into it
- Computer Vision and Pattern Recognition — 69 citations into it
- Natural Language Processing — 60 citations into it
- Representation & Self-Supervised Learning — 20 citations into it
- Model Architectures — 17 citations into it
- Optimization & Training — 10 citations into it
Whom Jinchao Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Ross B. Girshick
- Ruslan Salakhutdinov
- Sepp Hochreiter
Papers from Jinchao Zhang's perspective
Ordered by how strongly the researchers Jinchao Zhang 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- 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)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining (2022) — 160 citations
- GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling (2019) — 97 citations
- Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances (2021) — 67 citations
- Token-level Adaptive Training for Neural Machine Translation (2020) — 39 citations