Zhong-Qiu Wang
Signal Processing · 2018
A researcher in the Science corpus: 4 papers; trusts 50 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 79 citations into it; #887 of 7,572 by trust here, #1,299 by citations
- Artificial Intelligence — 34 citations into it; #12,265 of 35,345 by trust here, #17,776 by citations
- Speech & Audio — 27 citations into it; #791 of 1,076 by trust here, #769 by citations
- Computational Mechanics — 20 citations into it
- Cognitive Neuroscience — 17 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
Whom Zhong-Qiu Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John R. Hershey
- Jonathan Le Roux
- Zhuo Chen
- Yi Luo
- Francis R. Bach
- Hakan Erdogan
- Deliang Wang
- Radford M. Neal
- Emmanuel Vincent
- Dong Yu
Who trusts Zhong-Qiu Wang overall
- Jonathan Le Roux
- Eliya Nachmani
- Gordon Wichern
- Yi Luo
- Yossi Adi
- Lior Wolf
- Hyeong-Seok Choi
- Prem Seetharaman
- Shlomo E. Chazan
- Scott Wisdom
Papers from Zhong-Qiu Wang's perspective
Ordered by how strongly the researchers Zhong-Qiu Wang trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction (2018) — 134 citations
- Deep Learning Based Phase Reconstruction for Speaker Separation: A Trigonometric Perspective (2018) — 100 citations
- Alternative Objective Functions for Deep Clustering (2018) — 191 citations
- Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation (2018) — 253 citations