Haoran Zhang

Artificial Intelligence · with Ghassemi · 2020

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Representation & Self-Supervised Learning — 33 citations into it
• Molecular Biology — 24 citations into it
• Safety, Robustness & Interpretability — 23 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Natural Language Processing — 19 citations into it
• Computational Biology & Bioinformatics — 17 citations into it

Whom Haoran Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Kaiming He
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Jacob Devlin
9. Richard S. Zemel
10. David John Cameron MacKay

Who trusts Haoran Zhang overall

1. Silvio Amir
2. Mohammed Saeed
3. Laleh Seyyed-Kalantari
4. Federico Bianchi
5. Jan-Willem van de Meent
6. Pascal Sturmfels
7. Naser Ahmadi

Papers from Haoran Zhang's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Self-Supervised Contrastive Learning of Protein Representations By Mutual Information Maximization (2020) — 93 citations
• Hurtful words: quantifying biases in clinical contextual word embeddings (2020) — 206 citations