Howard Heaton

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it
• Computer Vision and Pattern Recognition — 58 citations into it
• Computational Mechanics — 29 citations into it
• Optimization & Training — 22 citations into it
• Model Architectures — 14 citations into it

Whom Howard Heaton trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Kaiming He
6. Yann LeCun
7. Jimmy Ba
8. Chelsea Finn
9. Ilya Sutskever
10. Shaojie Bai

Papers from Howard Heaton's perspective

Ordered by how strongly the researchers Howard Heaton 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. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• JFB: Jacobian-Free Backpropagation for Implicit Networks (2021) — 139 citations
• Learning to Optimize: A Primer and A Benchmark (2021) — 358 citations