Hang Zheng

Computational Theory and Mathematics · 2023

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 67 citations into it
• Molecular Biology — 64 citations into it
• Materials Chemistry — 36 citations into it
• Computational Chemistry & Drug Discovery — 24 citations into it
• Artificial Intelligence — 23 citations into it
• Computational Biology & Bioinformatics — 6 citations into it
• Natural Language Processing — 5 citations into it

Whom Hang Zheng trusts overall

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

1. R. Quiroga
2. David Ryan Koes
3. Kaiming He

Papers from Hang Zheng's perspective

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

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

Their papers

• Uni-Mol: A Universal 3D Molecular Representation Learning Framework (2023) — 625 citations
• Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking? (2023) — 47 citations
• Uni-Dock: GPU-Accelerated Docking Enables Ultralarge Virtual Screening. (2023) — 101 citations