Jack Parker-Holder

Artificial Intelligence · 2019–2024

A researcher in the Science corpus: 7 papers; trusts 157 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 253 citations into it
• Reinforcement Learning — 159 citations into it
• Computer Vision and Pattern Recognition — 87 citations into it
• Optimization & Training — 32 citations into it
• Management Science and Operations Research — 30 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Computational Theory and Mathematics — 22 citations into it
• Representation & Self-Supervised Learning — 14 citations into it

Whom Jack Parker-Holder trusts overall

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

1. J. Urgen Schmidhuber
2. John Schulman
3. Geoffrey E. Hinton
4. Richard S. Sutton
5. Yoshua Bengio
6. Diederik P. Kingma
7. Sergey Levine
8. Alex Krizhevsky
9. Radford M. Neal
10. Pieter Abbeel

Who trusts Jack Parker-Holder overall

1. Aldo Pacchiano
2. Liyuan Wang

Papers from Jack Parker-Holder's perspective

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

Their papers

• Ready Policy One: World Building Through Active Learning (2020) — 54 citations
• Same State, Different Task: Continual Reinforcement Learning without Interference (2021) — 62 citations
• Replay-Guided Adversarial Environment Design (2021) — 139 citations
• Learning to Score Behaviors for Guided Policy Optimization (2019) — 46 citations
• Genie: Generative Interactive Environments (2024) — 696 citations
• Human-Timescale Adaptation in an Open-Ended Task Space (2023) — 163 citations
• Effective Diversity in Population-Based Reinforcement Learning (2020) — 191 citations