Nelson Yalta
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 5 papers; trusts 61 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 132 citations into it; #16,653 of 35,345 by trust here, #5,059 by citations
- Natural Language Processing — 69 citations into it; #5,338 of 5,688 by trust here, #4,032 by citations
- Speech & Audio — 59 citations into it; #562 of 1,076 by trust here, #215 by citations
- Signal Processing — 56 citations into it; #4,462 of 7,572 by trust here, #981 by citations
- Model Architectures — 39 citations into it
- Computer Vision and Pattern Recognition — 31 citations into it
- Optimization & Training — 6 citations into it
Whom Nelson Yalta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Geoffrey E. Hinton
- Yoshua Bengio
- Dzmitry Bahdanau
- Diederik P. Kingma
- Yann LeCun
- Jimmy Ba
- Ilya Sutskever
- Kaiming He
- Alex Krizhevsky
Who trusts Nelson Yalta overall
Papers from Nelson Yalta's perspective
Ordered by how strongly the researchers Nelson Yalta 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- 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)
- ImageNet: A large-scale hierarchical image database
Their papers
- ESPnet: End-to-End Speech Processing Toolkit (2018) — 1,730 citations
- A Comparative Study on Transformer vs RNN in Speech Applications (2019) — 796 citations
- Multilingual Sequence-to-Sequence Speech Recognition: Architecture, Transfer Learning, and Language Modeling (2018) — 130 citations
- Improving Transformer-Based End-to-End Speech Recognition with Connectionist Temporal Classification and Language Model Integration (2019) — 231 citations
- ESPnet-ST: All-in-One Speech Translation Toolkit (2020) — 174 citations