Paul J. Kennedy

Artificial Intelligence · 2013–2019

A researcher in the Science corpus: 4 papers; trusts 107 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Model Architectures — 18 citations into it
• Molecular Biology — 12 citations into it
• Optimization & Training — 9 citations into it
• Information Systems — 5 citations into it

Whom Paul J. Kennedy trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Kaiming He
5. David E. Rumelhart
6. Isabelle M Guyon
7. Yann LeCun
8. Christian Szegedy
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Paul J. Kennedy overall

1. Sumanta Basu
2. Jun Chin Ang

Papers from Paul J. Kennedy's perspective

Ordered by how strongly the researchers Paul J. Kennedy 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Going deeper with convolutions
7. Gradient-based learning applied to document recognition
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges (2019) — 1,522 citations
• Training deep neural networks on imbalanced data sets (2016) — 452 citations
• A balanced iterative random forest for gene selection from microarray data (2013) — 81 citations
• Relational autoencoder for feature extraction (2017) — 212 citations