Zach Dwiel

Reinforcement Learning · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 22 citations into it
• Artificial Intelligence — 18 citations into it

Whom Zach Dwiel trusts overall

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

1. J. Urgen Schmidhuber
2. Volodymyr Mnih
3. Richard S. Sutton
4. Geoffrey E. Hinton
5. Irina Higgins
6. David R Ha
7. Diederik P. Kingma
8. Yoshua Bengio
9. Alex Graves
10. David Silver

Who trusts Zach Dwiel overall

1. Tonghan Wang

Papers from Zach Dwiel's perspective

Ordered by how strongly the researchers Zach Dwiel 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Deep Semantic Protein Representation for Annotation, Discovery, and Engineering (2018) — 21 citations
• Hierarchical Policy Learning is Sensitive to Goal Space Design (2019) — 15 citations