Qiankun Ding

Molecular Biology · 2023

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 29 citations into it
• Computational Chemistry & Drug Discovery — 12 citations into it
• Natural Language Processing — 5 citations into it

Whom Qiankun Ding trusts overall

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

1. Kaiming He
2. Johannes Klicpera
3. David Weininger
4. S. Parasuraman
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Diederik P. Kingma

Papers from Qiankun Ding's perspective

Ordered by how strongly the researchers Qiankun Ding 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. ImageNet classification with deep convolutional neural networks
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Language Models are Few-Shot Learners (Neural Information Processing Systems)

Their papers

• Uni-Mol: A Universal 3D Molecular Representation Learning Framework (2023) — 625 citations