Jacob Dumford

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Signal Processing — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Jacob Dumford trusts overall

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

1. Kaiming He
2. Alex Graves
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoshua Bengio
6. Tianyu Gu
7. Sebastian Eresheim
8. X. Zhang
9. Alex Krizhevsky
10. Ilya Sutskever

Papers from Jacob Dumford's perspective

Ordered by how strongly the researchers Jacob Dumford 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Backdooring Convolutional Neural Networks via Targeted Weight Perturbations (2018) — 136 citations