Stephen Ra

Computer Vision and Pattern Recognition · 2021–2023

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

• Computer Vision and Pattern Recognition — 10 citations into it

Whom Stephen Ra trusts overall

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

1. Pascal Vincent
2. Yoshua Bengio
3. Amos Bairoch
4. Geoffrey E. Hinton
5. Hugo Larochelle

Papers from Stephen Ra's perspective

Ordered by how strongly the researchers Stephen Ra 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. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Extracting and composing robust features with denoising autoencoders
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• OpenFold: retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization (2023) — 435 citations
• Function-guided protein design by deep manifold sampling (2021) — 35 citations