Michal Zajkac

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 76 citations into it
• Reinforcement Learning — 29 citations into it
• Meta & Continual Learning — 28 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Optimization & Training — 8 citations into it
• Cognitive Neuroscience — 6 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Michal Zajkac trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Tuomas Haarnoja
6. Kaiming He
7. Yann LeCun
8. Richard S. Sutton
9. Ilya Sutskever
10. Jimmy Ba

Papers from Michal Zajkac's perspective

Ordered by how strongly the researchers Michal Zajkac 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Continual World: A Robotic Benchmark For Continual Reinforcement Learning (2021) — 138 citations
• Disentangling Transfer in Continual Reinforcement Learning (2022) — 42 citations