Ehsan Variani

Artificial Intelligence · 2014–2020

A researcher in the Science corpus: 5 papers; trusts 55 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 83 citations into it; #11,834 of 35,345 by trust here, #9,369 by citations
• Signal Processing — 58 citations into it; #2,218 of 7,572 by trust here, #1,219 by citations
• Natural Language Processing — 38 citations into it; #3,080 of 5,688 by trust here, #5,214 by citations
• Speech & Audio — 37 citations into it; #405 of 1,076 by trust here, #371 by citations
• Model Architectures — 28 citations into it; #1,788 of 2,278 by trust here, #2,162 by citations
• Optimization & Training — 15 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it

Whom Ehsan Variani trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Frederick Jelinek
5. Patrick Kenny
6. Hasim Sak
7. Kaiming He
8. Alex Krizhevsky
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Ehsan Variani overall

1. Jinyu Li
2. Mirco Ravanelli
3. Rama Doddipatla
4. Peidong Wang
5. Zhongxin Bai
6. Tara N. Sainath
7. Yoshua Bengio
8. Shuai Wang
9. David Snyder
10. Raymond W. M. Ng

Papers from Ehsan Variani's perspective

Ordered by how strongly the researchers Ehsan Variani 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep neural networks for small footprint text-dependent speaker verification (2014) — 959 citations
• A Density Ratio Approach to Language Model Fusion in End-to-End Automatic Speech Recognition (2019) — 121 citations
• End-to-End Training of Acoustic Models for Large Vocabulary Continuous Speech Recognition with TensorFlow (2017) — 28 citations
• Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition (2017) — 213 citations
• Hybrid Autoregressive Transducer (HAT) (2020) — 174 citations