Ryan Steed
Artificial Intelligence · 2020
A researcher in the Science corpus: 1 paper; trusts 197 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 38 citations into it
- Computer Vision and Pattern Recognition — 28 citations into it
- Representation & Self-Supervised Learning — 17 citations into it
- Safety, Robustness & Interpretability — 17 citations into it
- Natural Language Processing — 14 citations into it
- Sociology and Political Science — 11 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Model Architectures — 6 citations into it
Whom Ryan Steed trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Tomas Mikolov
- Ting-Li Chen
- Diederik P. Kingma
- Latanya Sweeney
- Ilya Sutskever
- Yann LeCun
Who trusts Ryan Steed overall
Papers from Ryan Steed's perspective
Ordered by how strongly the researchers Ryan Steed trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (2020) — 186 citations