Y. Liu
Electrical and Electronic Engineering · Journal of Alloys and Compounds · 1998–2023
A researcher in the Science corpus: 86 papers; trusts 994 researchers and is trusted by 17 researchers here, as inferred from the citation graph.
Subfields
- Electrical and Electronic Engineering — 532 citations into it; #10,799 of 16,539 by trust here, #656 by citations
- Materials Chemistry — 490 citations into it
- Electronic, Optical and Magnetic Materials — 440 citations into it
- Computer Vision and Pattern Recognition — 257 citations into it; #7,846 of 21,575 by trust here, #9,079 by citations
- Mechanical Engineering — 256 citations into it; #8,096 of 8,300 by trust here, #1,144 by citations
- Biomedical Engineering — 239 citations into it; #10,472 of 10,734 by trust here, #924 by citations
- Artificial Intelligence — 227 citations into it; #29,027 of 35,345 by trust here, #13,760 by citations
- Aerospace Engineering — 189 citations into it; #4,713 of 6,421 by trust here, #1,543 by citations
Whom Y. Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ross B. Girshick
- Yoshua Bengio
- Diederik P. Kingma
- Karen Simonyan
- Yann LeCun
- Ilya Sutskever
- Andrew Zisserman
Who trusts Y. Liu overall
- Kenneth O. Stanley
- Mengyang Pu
- Xin Yao
- Yupei Wang
- Hui Li
- Xin-chun Zhang
- Jianzhong He
- Yun Liu
- Tabish Rashid
- Zhuo Su
Papers from Y. Liu's perspective
Ordered by how strongly the researchers Y. 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Learning Relaxed Deep Supervision for Better Edge Detection (2016) — 138 citations
- CNN-RNN: a large-scale hierarchical image classification framework (2017) — 144 citations
- Understand scene categories by objects: A semantic regularized scene classifier using Convolutional Neural Networks (2015) — 111 citations
- AnomalyNet: An Anomaly Detection Network for Video Surveillance (2019) — 317 citations
- From Few to More: Large-scale Dynamic Multiagent Curriculum Learning (2019) — 141 citations
- ExpeL: LLM Agents Are Experiential Learners (2023) — 699 citations
- High Band Degeneracy Contributes to High Thermoelectric Performance in p‐Type Half‐Heusler Compounds (2014) — 312 citations
- An Overview of Existing Algorithms for Resolving the 180° Ambiguity in Vector Magnetic Fields: Quantitative Tests with Synthetic Data (2006) — 269 citations
- Nitrogen-doped graphene as efficient metal-free electrocatalyst for oxygen reduction in fuel cells. (2010) — 3,704 citations
- The DARPA Twitter Bot Challenge (2016) — 408 citations
- Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns (2019) — 34 citations
- Review on carbon-based composite materials for capacitive deionization (2015) — 318 citations
- Reduced graphene oxide and activated carbon composites for capacitive deionization (2012) — 233 citations
- Shape‐Memory Polymer in Response to Solution (2008) — 216 citations
- Direct Growth of Flexible Carbon Nanotube Electrodes (2008) — 186 citations
- Porous carbon spheres via microwave-assisted synthesis for capacitive deionization (2015) — 147 citations
- 3D printing of smart materials: A review on recent progresses in 4D printing (2015) — 792 citations
- Synergistically Optimizing Electrical and Thermal Transport Properties of BiCuSeO via a Dual‐Doping Approach (2016) — 210 citations
- Conductive Mesocellular Silica–Carbon Nanocomposite Foams for Immobilization, Direct Electrochemistry, and Biosensing of Proteins (2007) — 169 citations
- Biocompatible graphene oxide-based glucose biosensors. (2010) — 652 citations