Yongmin Liu
Electronic, Optical and Magnetic Materials · Chemical Society Reviews · 2007–2021
A researcher in the Science corpus: 10 papers; trusts 40 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Electronic, Optical and Magnetic Materials — 216 citations into it; #1,407 of 2,886 by trust here, #1,060 by citations
- Atomic and Molecular Physics, and Optics — 142 citations into it
- Biomedical Engineering — 122 citations into it; #8,036 of 10,734 by trust here, #1,889 by citations
- Aerospace Engineering — 107 citations into it; #6,158 of 6,421 by trust here, #1,183 by citations
- Artificial Intelligence — 61 citations into it
- Materials Chemistry — 25 citations into it
- Molecular Biology — 19 citations into it
- Computer Vision and Pattern Recognition — 17 citations into it
Whom Yongmin Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John B. Pendry
- Xiang Zhang
- Diederik P. Kingma
- Costas M. Soukoulis
- Geoffrey E. Hinton
- Ulf Leonhardt
- Wei Ma
- N. Yu
- David Schurig
- John H. Holland
Who trusts Yongmin Liu overall
Papers from Yongmin Liu's perspective
Ordered by how strongly the researchers Yongmin 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
- Going deeper with convolutions
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Rectified Linear Units Improve Restricted Boltzmann Machines
- Attention is All you Need (Neural Information Processing Systems)
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Their papers
- Metasurfaces for manipulating surface plasmons (2013) — 163 citations
- Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials. (2018) — 807 citations
- Metamaterials: a new frontier of science and technology. (2011) — 1,011 citations
- Optical Negative Refraction in Bulk Metamaterials of Nanowires (2008) — 851 citations
- Interfacing photonics with artificial intelligence: an innovative design strategy for photonic structures and devices based on artificial neural networks (2021) — 58 citations
- Deep learning for the design of photonic structures (2020) — 960 citations
- A data-efficient self-supervised deep learning model for design and characterization of nanophotonic structures (2020)
- Probabilistic Representation and Inverse Design of Metamaterials Based on a Deep Generative Model with Semi‐Supervised Learning Strategy (2019) — 534 citations
- Circular dichroism metamirrors with near-perfect extinction (2016) — 258 citations
- Magnetic plasmon hybridization and optical activity at optical frequencies in metallic nanostructures (2007) — 210 citations