Jiani Zhang

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 53 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it; #13,733 of 35,345 by trust here, #9,369 by citations
• Graph Learning — 28 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it
• Natural Language Processing — 18 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Model Architectures — 16 citations into it
• Statistical and Nonlinear Physics — 10 citations into it; #4,660 of 10,127 by trust here, #6,156 by citations
• Molecular Biology — 8 citations into it; #6,779 of 17,773 by trust here, #14,176 by citations

Whom Jiani Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Sepp Hochreiter
5. Alex Graves
6. Yann LeCun
7. Alex Krizhevsky
8. Tomas Mikolov
9. Ilya Sutskever
10. J. Urgen Schmidhuber

Who trusts Jiani Zhang overall

1. Shalini Pandey
2. Chun-Kit Yeung
3. Hongwei Wang
4. Hoang NT
5. Xiao Wang
6. Ghodai M. Abdelrahman
7. Aritra Ghosh
8. Ziwei Zhang
9. Yuhui Ding
10. Mike Wu

Papers from Jiani Zhang's perspective

Ordered by how strongly the researchers Jiani Zhang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs (2018) — 641 citations
• MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding (2020) — 1,182 citations
• Dynamic Key-Value Memory Networks for Knowledge Tracing (2016) — 863 citations