Xiaogen Zhou
Molecular Biology · 2019–2022
A researcher in the Science corpus: 5 papers; trusts 40 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 178 citations into it; #13,655 of 17,773 by trust here, #14,509 by citations
- Materials Chemistry — 101 citations into it; #8,832 of 11,513 by trust here, #10,845 by citations
- Computational Biology & Bioinformatics — 97 citations into it
- Spectroscopy — 12 citations into it
- Computational Theory and Mathematics — 11 citations into it
- Artificial Intelligence — 9 citations into it
- AI for Physical Sciences — 5 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Xiaogen Zhou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yang Zhang
- Sheng Wang
- Jeffrey Skolnick
- Jinbo Xu
- Jianyi Yang
- Yang Li
- Chengxin Zhang
- Dong Xu
- Ambrish Roy
- Wei Zheng
Who trusts Xiaogen Zhou overall
Papers from Xiaogen Zhou's perspective
Ordered by how strongly the researchers Xiaogen Zhou trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
- Gradient-based learning applied to document recognition
- Highly accurate protein structure prediction with AlphaFold
- Long Short-Term Memory
- Automatic differentiation in PyTorch
Their papers
- Deducing high-accuracy protein contact-maps from a triplet of coevolutionary matrices through deep residual convolutional networks (2020) — 72 citations
- I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction (2022) — 417 citations
- MMpred: a distance-assisted multimodal conformation sampling for de novo protein structure prediction (2021) — 26 citations
- De novo Protein Structure Prediction by Coupling Contact With Distance Profile (2020) — 7 citations
- CGLFold: a contact-assisted de novo protein structure prediction using global exploration and loop perturbation sampling algorithm (2019) — 27 citations