Benjamin Shih

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it

Whom Benjamin Shih trusts overall

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

1. Diederik P. Kingma
2. Sepp Hochreiter
3. Herke Van Hoof
4. Yoshua Bengio
5. J. Urgen Schmidhuber
6. Geoffrey E. Hinton
7. Jimmy Ba
8. Ronald J. Williams
9. Dimitri P. Bertsekas
10. Yevgen Chebotar

Papers from Benjamin Shih's perspective

Ordered by how strongly the researchers Benjamin Shih 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. Long Short-Term Memory
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Soft robot perception using embedded soft sensors and recurrent neural networks (2019) — 595 citations
• Electronic skins and machine learning for intelligent soft robots (2020) — 642 citations