Xinjian Li
Artificial Intelligence · with Black · 2019–2022
A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 53 citations into it
- Speech & Audio — 35 citations into it
- Signal Processing — 25 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Xinjian Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Geoffrey E. Hinton
- Yoshua Bengio
- Ye Jia
- Diederik P. Kingma
- Xavier Glorot
- Aäron van den Oord
- Oriol Vinyals
- Alex Krizhevsky
- Ilya Sutskever
Papers from Xinjian Li's perspective
Ordered by how strongly the researchers Xinjian Li 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Multilingual Speech Recognition with Corpus Relatedness Sampling (2019) — 17 citations
- Textless Direct Speech-to-Speech Translation with Discrete Speech Representation (2022) — 36 citations
- Universal Phone Recognition with a Multilingual Allophone System (2020) — 172 citations