Pawel Ladosz

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Reinforcement Learning — 56 citations into it
• Management Science and Operations Research — 16 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it

Whom Pawel Ladosz trusts overall

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

1. J. Urgen Schmidhuber
2. Richard S. Sutton
3. Ronald J. Williams
4. Ian Osband
5. Geoffrey E. Hinton
6. Marc G. Bellemare
7. Marlos C. Machado
8. Andrew Barto
9. Yoshua Bengio
10. Diederik P. Kingma

Papers from Pawel Ladosz's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Exploration in Deep Reinforcement Learning: A Survey (2022) — 605 citations