Liam Collins

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Federated & Distributed Learning — 16 citations into it
• Optimization & Training — 9 citations into it
• Computational Mechanics — 8 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Meta & Continual Learning — 5 citations into it

Whom Liam Collins trusts overall

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

1. Yoshua Bengio
2. Nilesh Tripuraneni
3. Omiros Papaspiliopoulos
4. Massimiliano Pontil
5. Michael I. Jordan
6. Alex Krizhevsky
7. Tian Li
8. Geoffrey E. Hinton
9. Virginia Smith
10. Jeffrey Pennington

Who trusts Liam Collins overall

1. Jaehoon Oh
2. Yue Tan
3. Jianqing Zhang
4. Sangmook Kim
5. Guodong Long

Papers from Liam Collins's perspective

Ordered by how strongly the researchers Liam Collins 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Exploiting Shared Representations for Personalized Federated Learning (2021) — 1,173 citations