Chao Hu
Artificial Intelligence · 2010–2022
A researcher in the Science corpus: 7 papers; trusts 22 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 67 citations into it
- Control and Systems Engineering — 47 citations into it; #7,212 of 8,257 by trust here, #5,227 by citations
- Automotive Engineering — 43 citations into it
- Statistics and Probability — 38 citations into it
- Electrical and Electronic Engineering — 36 citations into it; #12,808 of 16,539 by trust here, #5,345 by citations
- Computer Vision and Pattern Recognition — 24 citations into it
- Management Science and Operations Research — 16 citations into it
- Computational Theory and Mathematics — 13 citations into it
Whom Chao Hu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- H. Xu
- Bhaskar Saha
- Simon S. Haykin
- Mark Schwabacher
- Sharif Rahman
- Byeng Dong Youn
- Ronald J. Williams
- Xiaoping Du
- Alex Smola
- George Eastman House
Who trusts Chao Hu overall
- Zhen Hu
- Xiaosong Hu
- Chong Zhang
- Yao He
- Qiang Miao
- Olga Fink
- Yaguo Lei
- Xiaoping Du
- Xingtao Liu
- Pin Lim
Papers from Chao Hu's perspective
Ordered by how strongly the researchers Chao Hu trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- 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)
- Human-level control through deep reinforcement learning
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A Multiscale Framework with Extended Kalman Filter for Lithium-Ion Battery SOC and Capacity Estimation (2010) — 471 citations
- Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life (2011) — 367 citations
- A Generalized Complementary Intersection Method (GCIM) for System Reliability Analysis (2011) — 66 citations
- Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries (2020) — 481 citations
- A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies (2022) — 355 citations
- A deep learning method for online capacity estimation of lithium-ion batteries (2019) — 340 citations
- A comparative study of probability estimation methods for reliability analysis (2011) — 68 citations