James Sharpnack

Artificial Intelligence · 2020

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 — 21 citations into it
• Information Systems — 12 citations into it
• Optimization & Training — 10 citations into it
• Model Architectures — 7 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom James Sharpnack trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Jimmy Ba
4. Robert Tibshirani
5. Kaiming He
6. Balázs Hidasi
7. Steffen Rendle
8. Alex Krizhevsky
9. Sergey Ioffe
10. Yoshua Bengio

Papers from James Sharpnack's perspective

Ordered by how strongly the researchers James Sharpnack 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. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Long Short-Term Memory
8. Dropout: a simple way to prevent neural networks from overfitting
9. Gradient-based learning applied to document recognition
10. Layer Normalization

Their papers

• SSE-PT: Sequential Recommendation Via Personalized Transformer (2020) — 307 citations