Andrew Lim

Artificial Intelligence · with Cao · 2019

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Model Architectures — 8 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Reinforcement Learning — 7 citations into it

Whom Andrew Lim trusts overall

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

1. Ronald J. Williams

Papers from Andrew Lim's perspective

Ordered by how strongly the researchers Andrew Lim 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Asynchronous Methods for Deep Reinforcement Learning
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. Gradient-based learning applied to document recognition

Their papers

• Learning Improvement Heuristics for Solving Routing Problems (2019) — 420 citations