Charles K. Nicholas

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Model Architectures — 11 citations into it
• Optimization & Training — 10 citations into it

Whom Charles K. Nicholas trusts overall

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

1. Peter J. Rousseeuw
2. Diederik P. Kingma
3. Kaiming He
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Ross B. Girshick
7. Yann LeCun
8. Christian Szegedy
9. Yoshua Bengio

Papers from Charles K. Nicholas's perspective

Ordered by how strongly the researchers Charles K. Nicholas 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Going deeper with convolutions
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Dropout: a simple way to prevent neural networks from overfitting
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Cluster Quality Analysis Using Silhouette Score (2020) — 854 citations
• Malware Detection by Eating a Whole EXE (2017) — 690 citations