Zeliang Liu
Mechanics of Materials · 2016–2020
A researcher in the Science corpus: 4 papers; trusts 40 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Mechanics of Materials — 54 citations into it; #3,087 of 6,291 by trust here, #2,477 by citations
- Computational Theory and Mathematics — 36 citations into it; #7,764 of 12,182 by trust here, #8,294 by citations
- Materials Chemistry — 25 citations into it
- Mechanical Engineering — 21 citations into it
- Computational Mechanics — 20 citations into it
- Artificial Intelligence — 19 citations into it
- Statistics and Probability — 17 citations into it
- Biomedical Engineering — 16 citations into it
Whom Zeliang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- J. Michel
- Julien Yvonnet
- Gregory J. Wagner
- Wing Kam Liu
- S. Forest
- Peter J. Rousseeuw
- Anthony Peirce
- Pierre Suquet
- Qi-Chang He
- V. Kouznetsova
Who trusts Zeliang Liu overall
Papers from Zeliang Liu's perspective
Ordered by how strongly the researchers Zeliang Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality (2017) — 525 citations
- Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials (2016) — 441 citations
- Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks (2020) — 434 citations
- Microstructural material database for self-consistent clustering analysis of elastoplastic strain softening materials (2018) — 178 citations