Tanel Alumäe

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 70 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #15,416 of 35,345 by trust here, #23,731 by citations
• Speech & Audio — 20 citations into it; #700 of 1,076 by trust here, #885 by citations
• Signal Processing — 13 citations into it; #5,780 of 7,572 by trust here, #5,829 by citations
• Natural Language Processing — 11 citations into it; #3,869 of 5,688 by trust here, #5,593 by citations
• Model Architectures — 10 citations into it; #1,581 of 2,278 by trust here, #2,243 by citations
• Evaluation & Benchmarks — 8 citations into it; #2,440 of 3,147 by trust here, #2,903 by citations
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Tanel Alumäe trusts overall

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

1. Daniel Povey
2. Yoshua Bengio
3. Kyunghyun Cho
4. Geoffrey E. Hinton
5. Kaiming He
6. Dzmitry Bahdanau
7. Anthony Rousseau
8. Xavier Glorot
9. Alex Krizhevsky
10. David Snyder

Who trusts Tanel Alumäe overall

1. Alexis Conneau
2. Hazel Doughty
3. Arun Babu
4. Antoine Yang
5. Alec Radford
6. Zhehuai Chen
7. Yu Zhang
8. Ivan Laptev
9. Alexei Baevski

Papers from Tanel Alumäe's perspective

Ordered by how strongly the researchers Tanel Alumäe 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• The 2016 BBN Georgian telephone speech keyword spotting system (2017) — 25 citations
• VOXLINGUA107: A Dataset for Spoken Language Recognition (2020) — 234 citations
• Bidirectional Recurrent Neural Network with Attention Mechanism for Punctuation Restoration (2016) — 197 citations