Zhen Zeng

Artificial Intelligence · with Cheng · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 48 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it; #15,080 of 35,345 by trust here, #16,771 by citations
• Speech & Audio — 33 citations into it
• Signal Processing — 32 citations into it; #6,576 of 7,572 by trust here, #6,591 by citations
• Generative Models — 22 citations into it
• Natural Language Processing — 22 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Model Architectures — 9 citations into it

Whom Zhen Zeng trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Kaiming He
5. Aäron van den Oord
6. Alex Krizhevsky
7. Nal Kalchbrenner
8. Jimmy Ba
9. Karen Simonyan
10. Alex Graves

Who trusts Zhen Zeng overall

1. Xu Tan
2. Tao Qin
3. Yanli Li
4. Ulme Wennberg
5. Jaehyeon Kim
6. Isaac Elias
7. Zhaoxi Mu
8. Jonathan Shen
9. Won Jang
10. Frank K. Soong

Papers from Zhen Zeng's perspective

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

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

Their papers

• Aligntts: Efficient Feed-Forward Text-to-Speech System Without Explicit Alignment (2020) — 63 citations
• LVCNet: Efficient Condition-Dependent Modeling Network for Waveform Generation (2021) — 18 citations
• Prosody Learning Mechanism for Speech Synthesis System Without Text Length Limit (2020) — 9 citations
• GraphTTS: Graph-to-Sequence Modelling in Neural Text-to-Speech (2020) — 22 citations