Atil Iscen

Artificial Intelligence · 2014–2025

A researcher in the Science corpus: 7 papers; trusts 41 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 78 citations into it; #27,188 of 35,345 by trust here, #17,776 by citations
• Reinforcement Learning — 68 citations into it; #2,049 of 2,242 by trust here, #1,037 by citations
• Biomedical Engineering — 48 citations into it; #4,183 of 10,734 by trust here, #2,938 by citations
• Control and Systems Engineering — 38 citations into it; #7,316 of 8,257 by trust here, #1,139 by citations
• Computer Vision and Pattern Recognition — 33 citations into it; #19,617 of 21,575 by trust here, #7,852 by citations
• Optimization & Training — 13 citations into it
• Robotics & Control — 10 citations into it; #523 of 609 by trust here, #238 by citations

Whom Atil Iscen trusts overall

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

1. John Schulman
2. Sergey Levine
3. Jan Peters
4. Richard S. Sutton
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. Pieter Abbeel
8. Yoshua Bengio
9. Alex Krizhevsky
10. E. Todorov

Who trusts Atil Iscen overall

1. Jie Tan
2. Julian Ibarz
3. Jemin Hwangbo
4. Yuxiang Yang
5. Ken Caluwaerts
6. Ashish Kumar
7. Chelsea Finn
8. Sehoon Ha
9. Sergey Levine
10. Tingnan Zhang

Papers from Atil Iscen's perspective

Ordered by how strongly the researchers Atil Iscen 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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. Et al
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Sim-to-Real: Learning Agile Locomotion For Quadruped Robots (2018) — 981 citations
• Policies Modulating Trajectory Generators (2018) — 151 citations
• Data Efficient Reinforcement Learning for Legged Robots (2019) — 169 citations
• NoRML: No-Reward Meta Learning (2019) — 29 citations
• Optimizing Simulations with Noise-Tolerant Structured Exploration (2018) — 12 citations
• Gemini Robotics: Bringing AI into the Physical World (2025) — 385 citations
• Design and control of compliant tensegrity robots through simulation and hardware validation (2014) — 294 citations