Arshdeep Sekhon

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Molecular Biology — 20 citations into it
• Natural Language Processing — 18 citations into it
• Model Architectures — 14 citations into it
• Materials Chemistry — 7 citations into it

Whom Arshdeep Sekhon trusts overall

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

1. Alex Graves
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Ilya Sutskever
5. Diederik P. Kingma
6. Oriol Vinyals
7. Alex Krizhevsky
8. Yann LeCun
9. Andrew McCallum
10. Jimmy Ba

Papers from Arshdeep Sekhon's perspective

Ordered by how strongly the researchers Arshdeep Sekhon trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Neural Message Passing for Multi-Label Classification (2019) — 41 citations
• Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin (2017) — 100 citations