Jan Issac

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Reinforcement Learning — 21 citations into it
• Robotics & Control — 11 citations into it

Whom Jan Issac trusts overall

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

1. Marc Peter Deisenroth
2. Jan Peters
3. Sergey Levine

Papers from Jan Issac's perspective

Ordered by how strongly the researchers Jan Issac 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. Proximal Policy Optimization Algorithms (arXiv.org)
4. End-to-End Training of Deep Visuomotor Policies
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Et al

Their papers

• Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience (2018) — 623 citations
• Real-Time Perception Meets Reactive Motion Generation (2017) — 124 citations