Xiaojun Yao

Computational Theory and Mathematics · 2019

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

• Computational Theory and Mathematics — 14 citations into it
• Molecular Biology — 14 citations into it
• Materials Chemistry — 6 citations into it

Whom Xiaojun Yao trusts overall

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

1. Matthew D. Zeiler

Papers from Xiaojun Yao's perspective

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

1. ADADELTA: An Adaptive Learning Rate Method
2. Deep Learning
3. Convolutional Networks on Graphs for Learning Molecular Fingerprints
4. Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data
5. Workshop on Unsupervised and Transfer Learning Deep Learning of Representations for Unsupervised and Transfer Learning
6. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading
7. Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise
8. Extended-Connectivity Fingerprints
9. Virtual screening of chemical libraries
10. PubChem Substance and Compound databases

Their papers

• DeepDock: Enhancing Ligand-protein Interaction Prediction by a Combination of Ligand and Structure Information (2019) — 41 citations