Seungjin Lee

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it; #34,865 of 35,345 by trust here, #23,731 by citations
• Signal Processing — 25 citations into it; #7,508 of 7,572 by trust here, #4,560 by citations
• Speech & Audio — 20 citations into it; #1,058 of 1,076 by trust here, #856 by citations
• Model Architectures — 12 citations into it

Whom Seungjin Lee trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Graves

Who trusts Seungjin Lee overall

1. Jinyu Li

Papers from Seungjin Lee's perspective

Ordered by how strongly the researchers Seungjin Lee trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
3. Large Scale Distributed Deep Networks
4. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
5. Attention-Based Models for Speech Recognition
6. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks
7. Sequence Transduction with Recurrent Neural Networks
8. Gradient-based learning applied to document recognition
9. Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin
10. ImageNet classification with deep convolutional neural networks

Their papers

• Large-Scale Multilingual Speech Recognition with a Streaming End-to-End Model (2019) — 194 citations
• No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models (2017) — 54 citations