Mingjiang Wang

Signal Processing · with Nicolson · 2020

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 19 citations into it
• Artificial Intelligence — 10 citations into it
• Computational Mechanics — 9 citations into it
• Cognitive Neuroscience — 7 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Mingjiang Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rainer Martin
2. Israel Cohen
3. Jimmy Ba
4. Diederik P. Kingma
5. Geoffrey E. Hinton
6. Cees H. Taal
7. Richard Christian Hendriks
8. Vinod Nair
9. Timo Gerkmann

Papers from Mingjiang Wang's perspective

Ordered by how strongly the researchers Mingjiang Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Rectified Linear Units Improve Restricted Boltzmann Machines
3. Layer Normalization
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• DeepMMSE: A Deep Learning Approach to MMSE-Based Noise Power Spectral Density Estimation (2020) — 131 citations