Alex Gain

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 57 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Meta & Continual Learning — 18 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Optimization & Training — 11 citations into it
• Efficiency & Compression — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Alex Gain trusts overall

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

1. Alex Krizhevsky
2. R. M. French
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Kaiming He
6. Yoshua Bengio
7. Yann LeCun
8. Jimmy Ba
9. Ilya Sutskever
10. Jia Deng

Who trusts Alex Gain overall

1. Yingcong Li

Papers from Alex Gain's perspective

Ordered by how strongly the researchers Alex Gain 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Compressing GANs using Knowledge Distillation (2019) — 87 citations
• Understanding Catastrophic Forgetting and Remembering in Continual Learning with Optimal Relevance Mapping (2021) — 80 citations