Abhay Singh

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Graph Learning — 19 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Statistical and Nonlinear Physics — 16 citations into it
• Molecular Biology — 5 citations into it

Whom Abhay Singh trusts overall

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

1. Geoffrey E. Hinton
2. Jure Leskovec
3. Yoshua Bengio
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Yann LeCun
7. Kaiming He
8. Ilya Sutskever
9. Ruslan Salakhutdinov
10. J. Urgen Schmidhuber

Papers from Abhay Singh's perspective

Ordered by how strongly the researchers Abhay Singh 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Combining Label Propagation and Simple Models Out-performs Graph Neural Networks (2020) — 328 citations
• Better Set Representations For Relational Reasoning (2020) — 22 citations