M. Whitehill

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it; #28,422 of 35,345 by trust here, #31,361 by citations
• Speech & Audio — 7 citations into it
• Signal Processing — 6 citations into it; #6,079 of 7,572 by trust here, #6,591 by citations

Whom M. Whitehill trusts overall

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

1. Yuxuan Wang
2. L. V. D. van der Maaten
3. Geoffrey E. Hinton
4. Daniel W. Griffin
5. Yaroslav Ganin
6. Harsh Rai
7. Shuang Ma
8. Yanyao Bian
9. R. Skerry-Ryan
10. Victor S. Lempitsky

Who trusts M. Whitehill overall

1. Zhaoxi Mu
2. Xiaochun An
3. Frank K. Soong
4. Xu Tan
5. Liumeng Xue
6. Lei Xie
7. Xinyu Yang
8. Tao Qin

Papers from M. Whitehill's perspective

Ordered by how strongly the researchers M. Whitehill 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. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Multi-Reference Neural TTS Stylization with Adversarial Cycle Consistency (2019) — 35 citations