Breandan Considine

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Generative Models — 18 citations into it
• Artificial Intelligence — 15 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Breandan Considine trusts overall

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

1. Diederik P. Kingma
2. Yann LeCun
3. Kaiming He

Papers from Breandan Considine's perspective

Ordered by how strongly the researchers Breandan Considine 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. Gradient-based learning applied to document recognition
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. GENERATIVE ADVERSARIAL NETS
5. ImageNet classification with deep convolutional neural networks
6. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
7. Improved Techniques for Training GANs
8. Learning Multiple Layers of Features from Tiny Images
9. Long Short-Term Memory
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Multi-objective training of Generative Adversarial Networks with multiple discriminators (2019) — 72 citations