Wei Zou
Artificial Intelligence · with Li · 2018–2021
A researcher in the Science corpus: 5 papers; trusts 56 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 121 citations into it; #20,378 of 35,345 by trust here, #11,072 by citations
- Signal Processing — 75 citations into it; #4,198 of 7,572 by trust here, #1,629 by citations
- Speech & Audio — 70 citations into it; #734 of 1,076 by trust here, #528 by citations
- Natural Language Processing — 44 citations into it
- Model Architectures — 23 citations into it
- Representation & Self-Supervised Learning — 21 citations into it; #3,060 of 3,145 by trust here, #2,516 by citations
- Computer Vision and Pattern Recognition — 14 citations into it
- Optimization & Training — 8 citations into it
Whom Wei Zou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- J. Urgen Schmidhuber
- Diederik P. Kingma
- Jimmy Ba
- Geoffrey E. Hinton
- Yoshua Bengio
- Dzmitry Bahdanau
- William Chan
- Ilya Sutskever
- Alex Krizhevsky
Who trusts Wei Zou overall
Papers from Wei Zou's perspective
Ordered by how strongly the researchers Wei Zou trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10, 000 Hours of Transcribed Audio (2021) — 607 citations
- A Further Study of Unsupervised Pretraining for Transformer Based Speech Recognition (2020) — 32 citations
- Improving Transformer-based Speech Recognition Using Unsupervised Pre-training (2019) — 106 citations
- Didispeech: A Large Scale Mandarin Speech Corpus (2020) — 63 citations
- Comparable Study Of Modeling Units For End-To-End Mandarin Speech Recognition (2018) — 35 citations