James She

Artificial Intelligence · with Jeon · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 54 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it; #7,578 of 21,575 by trust here, #12,689 by citations
• Recommender Systems — 9 citations into it
• Computer Networks and Communications — 8 citations into it
• Information Systems — 7 citations into it; #1,924 of 8,771 by trust here, #4,518 by citations
• Electrical and Electronic Engineering — 6 citations into it
• Natural Language Processing — 6 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom James She trusts overall

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

1. Ruslan Salakhutdinov
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Michael J. Pazzani
5. Yoshua Bengio
6. Ken Lang
7. Andriy Mnih
8. Alex Krizhevsky
9. Max Welling
10. Radford M. Neal

Who trusts James She overall

1. Hao Wang
2. Aminu Da’u
3. Maurizio Ferrari Dacrema
4. Zeynep Batmaz
5. Dit-Yan Yeung
6. Jianxin Ma
7. Yi Tay
8. Naomie Binti Salim

Papers from James She's perspective

Ordered by how strongly the researchers James She 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. Going deeper with convolutions

Their papers

• BLE Beacons for Internet of Things Applications: Survey, Challenges, and Opportunities (2018) — 315 citations
• Collaborative Variational Autoencoder for Recommender Systems (2017) — 458 citations