Philip Bontrager

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it; #35,111 of 35,345 by trust here, #19,018 by citations

Whom Philip Bontrager trusts overall

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

1. Tom Schaul

Who trusts Philip Bontrager overall

1. Jeff Clune

Papers from Philip Bontrager's perspective

Ordered by how strongly the researchers Philip Bontrager trusts endorse each paper. Same corpus, a different order for every researcher.

1. Asynchronous Methods for Deep Reinforcement Learning
2. Et al
3. Curriculum learning
4. The Arcade Learning Environment: An Evaluation Platform for General Agents
5. ImageNet classification with deep convolutional neural networks
6. Hindsight Experience Replay
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. ViZDoom: A Doom-based AI research platform for visual reinforcement learning
9. Long Short-Term Memory
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation (2018) — 205 citations
• The Llama 3 Herd of Models (2024) — 17,085 citations