Thomas Schmied

Reinforcement Learning · 2022

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

Subfields

• Reinforcement Learning — 36 citations into it

Whom Thomas Schmied trusts overall

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

1. Richard S. Sutton
2. J. Urgen Schmidhuber
3. Sepp Hochreiter
4. Geoffrey E. Hinton
5. Volodymyr Mnih
6. Yoshua Bengio
7. Alex Krizhevsky
8. Diederik P. Kingma
9. Andrew Barto
10. Yann LeCun

Papers from Thomas Schmied's perspective

Ordered by how strongly the researchers Thomas Schmied 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Reinforcement Learning: An Introduction
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning (2022) — 19 citations