John M. Pearson
Cognitive Neuroscience · 2011–2019
A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 54 citations into it
- Artificial Intelligence — 29 citations into it
- Reinforcement Learning — 26 citations into it
- Management Science and Operations Research — 11 citations into it
- Safety Research — 9 citations into it
Whom John M. Pearson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from John M. Pearson's perspective
Ordered by how strongly the researchers John M. Pearson trusts endorse each paper. Same corpus, a different order for every researcher.
- Reinforcement Learning: An Introduction
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- A Neural Substrate of Prediction and Reward
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)