Heng Lu

Artificial Intelligence · 2013–2020

A researcher in the Science corpus: 9 papers; trusts 97 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 148 citations into it; #16,771 of 35,345 by trust here, #10,798 by citations
• Signal Processing — 90 citations into it
• Speech & Audio — 78 citations into it
• Natural Language Processing — 66 citations into it
• Computer Vision and Pattern Recognition — 43 citations into it
• Model Architectures — 35 citations into it
• Generative Models — 17 citations into it
• Optimization & Training — 6 citations into it

Whom Heng Lu trusts overall

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

1. Heiga Zen
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Graves
5. Diederik P. Kingma
6. Keiichi Tokuda
7. Aäron van den Oord
8. Ilya Sutskever
9. Oriol Vinyals
10. Alex Krizhevsky

Who trusts Heng Lu overall

1. Zhaoxi Mu
2. Igor Jauk
3. Zhizheng Wu
4. Xu Tan
5. Heiga Zen
6. Xinyu Yang
7. Yuchen Fan
8. Qiao Tian
9. Frank K. Soong
10. Yao Qian

Papers from Heng Lu's perspective

Ordered by how strongly the researchers Heng Lu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• DurIAN: Duration Informed Attention Network For Multimodal Synthesis (2019) — 119 citations
• FeatherTTS: Robust and Efficient attention based Neural TTS (2020) — 5 citations
• On the localness modeling for the self-attention based end-to-end speech synthesis (2020) — 32 citations
• DurIAN: Duration Informed Attention Network for Speech Synthesis (2020) — 80 citations
• FeatherWave: An efficient high-fidelity neural vocoder with multi-band linear prediction (2020) — 22 citations
• AdaDurIAN: Few-shot Adaptation for Neural Text-to-Speech with DurIAN (2020) — 27 citations
• Deep Feed-Forward Sequential Memory Networks for Speech Synthesis (2018) — 14 citations
• Linear Networks Based Speaker Adaptation for Speech Synthesis (2018) — 14 citations
• Combining a vector space representation of linguistic context with a deep neural network for text-to-speech synthesis (2013) — 64 citations