Walter A. Talbott

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 182 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 53 citations into it
• Artificial Intelligence — 46 citations into it
• Model Architectures — 24 citations into it
• Generative Models — 23 citations into it
• Optimization & Training — 12 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Walter A. Talbott trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Yann LeCun
6. Ilya Sutskever
7. Kaiming He
8. Jimmy Ba
9. Max Welling
10. Sergey Ioffe

Papers from Walter A. Talbott's perspective

Ordered by how strongly the researchers Walter A. Talbott trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• An Attention Free Transformer (2021) — 186 citations
• Adversarial Fisher Vectors for Unsupervised Representation Learning (2019) — 9 citations