Min Ma
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 5 papers; trusts 21 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 189 citations into it; #34,256 of 35,345 by trust here, #14,181 by citations
- Speech & Audio — 132 citations into it
- Signal Processing — 105 citations into it; #7,515 of 7,572 by trust here, #3,913 by citations
- Model Architectures — 18 citations into it
Whom Min Ma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Geoffrey E. Hinton
- Yoshua Bengio
- Sepp Hochreiter
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Ilya Sutskever
- Alex Krizhevsky
- Mark John Francis Gales
- Yann LeCun
Who trusts Min Ma overall
Papers from Min Ma's perspective
Ordered by how strongly the researchers Min Ma trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech (2022) — 651 citations
- BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition (2021) — 208 citations
- Scaling End-to-End Models for Large-Scale Multilingual ASR (2021) — 86 citations
- XTREME-S: Evaluating Cross-lingual Speech Representations (2022) — 27 citations
- Improving Streaming Automatic Speech Recognition with Non-Streaming Model Distillation on Unsupervised Data (2020) — 26 citations