James Weng

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 53 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #28,641 of 35,345 by trust here, #23,731 by citations
• Reinforcement Learning — 19 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it; #17,606 of 21,575 by trust here, #15,529 by citations
• Representation & Self-Supervised Learning — 5 citations into it

Whom James Weng trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yann LeCun
4. Volodymyr Mnih
5. John Schulman
6. Yoshua Bengio
7. Richard S. Sutton
8. Jimmy Ba
9. Ronald J. Williams
10. Alex Krizhevsky

Who trusts James Weng overall

1. Eric Crawford
2. Xingyu Lin
3. Shervin Minaee
4. Yuhang Song
5. Tejas D. Kulkarni

Papers from James Weng's perspective

Ordered by how strongly the researchers James Weng 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Unsupervised Video Object Segmentation for Deep Reinforcement Learning (2018) — 72 citations