Thiel Fellowship

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it
• Optimization & Training — 7 citations into it

Whom Thiel Fellowship trusts overall

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

1. Diederik P. Kingma
2. Jimmy Ba
3. Yangqing Jia
4. Shun-ichi Amari
5. Geoffrey E. Hinton
6. Dimitri P. Bertsekas
7. Sergey Ioffe
8. Yoshua Bengio

Papers from Thiel Fellowship's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Visualizing Deep Network Training Trajectories with PCA (2016)