Jun Ma
Artificial Intelligence · with Chen · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 49 citations into it; #24,057 of 35,345 by trust here, #12,083 by citations
- Speech & Audio — 35 citations into it
- Signal Processing — 32 citations into it; #5,097 of 7,572 by trust here, #1,669 by citations
- Natural Language Processing — 22 citations into it
- Generative Models — 15 citations into it
- Computer Vision and Pattern Recognition — 11 citations into it
Whom Jun Ma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Wei Ping
- Alan W. Black
- Geoffrey E. Hinton
- Yoshua Bengio
- Kainan Peng
- Ashish Vaswani
Who trusts Jun Ma overall
Papers from Jun Ma's perspective
Ordered by how strongly the researchers Jun Ma trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- WaveNet: A Generative Model for Raw Audio
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- Flow-TTS: A Non-Autoregressive Network for Text to Speech Based on Flow (2020) — 117 citations
- EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture (2020) — 46 citations
- Cross-Lingual, Multi-Speaker Text-To-Speech Synthesis Using Neural Speaker Embedding (2019) — 61 citations