Lisa Zhang

Artificial Intelligence · 2018

A researcher in the Science corpus: 3 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it
• Natural Language Processing — 15 citations into it
• Optimization & Training — 13 citations into it
• Model Architectures — 12 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Lisa Zhang trusts overall

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

1. Sepp Hochreiter
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. J. Urgen Schmidhuber
6. Alex Graves
7. Yujia Li
8. Ilya Sutskever
9. Oriol Vinyals
10. Alex Krizhevsky

Papers from Lisa Zhang's perspective

Ordered by how strongly the researchers Lisa Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Inference in Probabilistic Graphical Models by Graph Neural Networks (2018) — 110 citations
• Reviving and Improving Recurrent Back-Propagation (2018) — 140 citations
• Neural Guided Constraint Logic Programming for Program Synthesis (2018) — 35 citations