Joel Joseph

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 5 citations into it; #25,267 of 35,345 by trust here, #28,481 by citations
• Computer Vision and Pattern Recognition — 5 citations into it; #15,520 of 21,575 by trust here, #18,266 by citations

Whom Joel Joseph trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Sylvestre-Alvise Rebuffi
4. Matthew Riemer
5. Corinna Cortes
6. Geoffrey E. Hinton
7. Alexander Kolesnikov
8. Yoshua Bengio
9. Jia Deng
10. Diederik P. Kingma

Who trusts Joel Joseph overall

1. Lucas Caccia
2. Yisheng Song
3. Yichen Wu
4. Haeyong Kang
5. Joelle Pineau
6. Ting-Yuan Wang
7. Hong Wang
8. Rusty John Lloyd Rodriguez Mina
9. Hyuntak Cha

Papers from Joel Joseph's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. ImageNet: A large-scale hierarchical image database
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Et al

Their papers

• Reproducibility Report: La-MAML: Look-ahead Meta Learning for Continual Learning (2021) — 77 citations