Pierre-Alexandre Kamienny
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 68 citations into it
- Reinforcement Learning — 62 citations into it
- Computational Theory and Mathematics — 16 citations into it
- Game & Decision Theory — 14 citations into it
- Control and Systems Engineering — 13 citations into it
- Computer Vision and Pattern Recognition — 11 citations into it
- Mechanical Engineering — 6 citations into it
- Model Architectures — 6 citations into it
Whom Pierre-Alexandre Kamienny trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sam Wiseman
- S. Udrescu
- Tabish Rashid
- Marta Garnelo
- Ashish Vaswani
- Geoffrey E. Hinton
- Richard S. Sutton
- Diederik P. Kingma
- Ilya Sutskever
- Yoshua Bengio
Papers from Pierre-Alexandre Kamienny's perspective
Ordered by how strongly the researchers Pierre-Alexandre Kamienny trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Human-level control through deep reinforcement learning
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
Their papers
- End-to-end symbolic regression with transformers (2022) — 295 citations
- FACMAC: Factored Multi-Agent Centralised Policy Gradients (2020) — 370 citations
- Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control (2020) — 100 citations