Tung-Yu Wu

Artificial Intelligence · 2015

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #24,388 of 35,345 by trust here, #26,682 by citations
• Statistics and Probability — 9 citations into it; #8,986 of 12,932 by trust here, #7,914 by citations

Whom Tung-Yu Wu trusts overall

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

1. Geoffrey E. Hinton
2. Michael G. B. Blum
3. Paul Marjoram
4. Yann LeCun
5. MARK A. Beaumont
6. Paul Joyce
7. Paul Fearnhead
8. Anne-Laure Boulesteix
9. Yoshua Bengio
10. Scott Anthony Sisson

Who trusts Tung-Yu Wu overall

1. Pablo de Castro
2. Daniel R. Schrider
3. David S. Greenberg
4. Stefan T. Radev

Papers from Tung-Yu Wu's perspective

Ordered by how strongly the researchers Tung-Yu Wu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Dropout: a simple way to prevent neural networks from overfitting
6. Long Short-Term Memory
7. This PDF file includes: Materials and Methods
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network (2015) — 158 citations