Fred Richardson

Artificial Intelligence · 2008–2015

A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #10,401 of 35,345 by trust here, #15,866 by citations
• Signal Processing — 25 citations into it; #1,871 of 7,572 by trust here, #2,743 by citations
• Speech & Audio — 11 citations into it
• Natural Language Processing — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Fred Richardson trusts overall

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

1. Daniel Garcia-Romero
2. Najim Dehak
3. Geoffrey E. Hinton
4. Li Deng
5. Hynek Hermansky
6. Yu Zhang
7. Daniel Povey
8. Yun Lei
9. Ignacio Lopez-Moreno
10. Tara N. Sainath

Who trusts Fred Richardson overall

1. Zhongxin Bai
2. Mirco Ravanelli
3. David Snyder
4. Yoshua Bengio
5. Xiao-Lei Zhang
6. Ehud Ben-Reuven
7. Ma Jin
8. Shi-Xiong Zhang
9. Baoguang Shi
10. Taira Tsuchiya

Papers from Fred Richardson's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Deep Neural Network Approaches to Speaker and Language Recognition (2015) — 434 citations
• A unified deep neural network for speaker and language recognition (2015) — 163 citations
• The MITLL NIST LRE 2007 language recognition system (2008) — 41 citations