Liang Gao
Computational Theory and Mathematics · IEEE transactions on industrial electronics (1982. Print) · 2009–2019
A researcher in the Science corpus: 14 papers; trusts 106 researchers and is trusted by 35 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 82 citations into it
- Civil and Structural Engineering — 74 citations into it
- Statistics and Probability — 72 citations into it
- Mechanics of Materials — 62 citations into it; #1,820 of 6,291 by trust here, #1,848 by citations
- Control and Systems Engineering — 49 citations into it; #1,565 of 8,257 by trust here, #1,372 by citations
- Artificial Intelligence — 41 citations into it; #31,133 of 35,345 by trust here, #24,417 by citations
- Mechanical Engineering — 27 citations into it
- Industrial and Manufacturing Engineering — 22 citations into it; #244 of 2,521 by trust here, #556 by citations
Whom Liang Gao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Imed Kacem
- Xiaoping Du
- Yoshua Bengio
- Yann LeCun
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yaguo Lei
- Karen Simonyan
- Michael Y. Wang
Who trusts Liang Gao overall
- Long Wen
- Xinyu Li
- Rui Yang
- Stjepan Oreski
- K. Gao
- Maroua Nouiri
- Te Han
- Shen Zhang
- Mohammadreza Iman
- Imran Ali Chaudhry
Papers from Liang Gao's perspective
Ordered by how strongly the researchers Liang Gao 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
Their papers
- An optimal shifting vector approach for efficient probabilistic design (2013) — 96 citations
- A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis (2019) — 927 citations
- A transfer convolutional neural network for fault diagnosis based on ResNet-50 (2019) — 677 citations
- A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method (2018) — 1,795 citations
- Topology optimization of shell-infill structures using a distance regularized parametric level-set method (2018) — 51 citations
- Topology optimization for functionally graded cellular composites with metamaterials by level sets (2018) — 191 citations
- An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem (2016) — 535 citations
- A local Kriging approximation method using MPP for reliability-based design optimization (2016) — 134 citations
- An important boundary sampling method for reliability-based design optimization using kriging model (2015) — 97 citations
- A level set method for topological shape optimization of 3D structures with extrusion constraints (2015) — 70 citations
- An efficient method for reliability analysis under epistemic uncertainty based on evidence theory and support vector regression (2015) — 52 citations
- A local adaptive sampling method for reliability-based design optimization using Kriging model (2014) — 147 citations
- An effective genetic algorithm for the flexible job-shop scheduling problem (2011) — 478 citations
- An effective hybrid particle swarm optimization algorithm for multi-objective flexible job-shop scheduling problem (2009) — 528 citations