Yanzhang He

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 9 papers; trusts 70 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 152 citations into it; #14,894 of 35,345 by trust here, #4,956 by citations
• Signal Processing — 95 citations into it; #3,286 of 7,572 by trust here, #829 by citations
• Speech & Audio — 80 citations into it; #532 of 1,076 by trust here, #350 by citations
• Natural Language Processing — 59 citations into it
• Model Architectures — 47 citations into it; #2,087 of 2,278 by trust here, #1,070 by citations
• Optimization & Training — 13 citations into it

Whom Yanzhang He trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Tara N. Sainath
4. Sepp Hochreiter
5. Rohit Prabhavalkar
6. J. Urgen Schmidhuber
7. Yoshua Bengio
8. Diederik P. Kingma
9. Ilya Sutskever
10. Oriol Vinyals

Who trusts Yanzhang He overall

1. Jinyu Li
2. Tara N. Sainath
3. Rohit Prabhavalkar
4. Wei Han
5. Chung-Cheng Chiu
6. Bo Li
7. Yu Zhang
8. Khe Chai Sim
9. Jiahui Yu
10. Ruoming Pang

Papers from Yanzhang He's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling (2019) — 215 citations
• Streaming End-to-end Speech Recognition for Mobile Devices (2018) — 676 citations
• A Streaming On-Device End-To-End Model Surpassing Server-Side Conventional Model Quality and Latency (2020) — 228 citations
• A Better and Faster end-to-end Model for Streaming ASR (2020) — 133 citations
• Streaming small-footprint keyword spotting using sequence-to-sequence models (2017) — 96 citations
• Two-Pass End-to-End Speech Recognition (2019) — 163 citations
• An Attention-Based Joint Acoustic and Text on-Device End-To-End Model (2020) — 16 citations
• Deep neural network based spectral feature mapping for robust speech recognition (2015) — 66 citations
• Less is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging (2020) — 37 citations