Trevor Ablett

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it
• Reinforcement Learning — 16 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Robotics & Control — 8 citations into it
• Optimization & Training — 6 citations into it

Whom Trevor Ablett trusts overall

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

1. Jiakai Zhang
2. Diederik P. Kingma
3. Kyunghyun Cho
4. Jimmy Ba
5. Scott Fujimoto
6. John Schulman
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Sergey Levine
10. Ishaan Gulrajani

Who trusts Trevor Ablett overall

1. Ajay Mandlekar
2. Danfei Xu

Papers from Trevor Ablett's perspective

Ordered by how strongly the researchers Trevor Ablett 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. GENERATIVE ADVERSARIAL NETS
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Fighting Failures with FIRE: Failure Identification to Reduce Expert Burden in Intervention-Based Learning (2020) — 9 citations