Annie Xie

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 7 papers; trusts 429 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 196 citations into it; #6,608 of 35,345 by trust here, #4,772 by citations
• Reinforcement Learning — 143 citations into it; #1,321 of 2,242 by trust here, #978 by citations
• Computer Vision and Pattern Recognition — 127 citations into it; #11,953 of 21,575 by trust here, #6,206 by citations
• Control and Systems Engineering — 93 citations into it; #1,890 of 8,257 by trust here, #491 by citations
• Representation & Self-Supervised Learning — 47 citations into it
• Robotics & Control — 40 citations into it; #211 of 609 by trust here, #126 by citations
• Meta & Continual Learning — 24 citations into it; #832 of 1,041 by trust here, #409 by citations
• Biomedical Engineering — 23 citations into it

Whom Annie Xie trusts overall

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

1. Sergey Levine
2. Chelsea Finn
3. Pieter Abbeel
4. Diederik P. Kingma
5. J. Urgen Schmidhuber
6. Geoffrey E. Hinton
7. Richard S. Sutton
8. Yoshua Bengio
9. Alex Krizhevsky
10. John Schulman

Who trusts Annie Xie overall

1. Chelsea Finn
2. Sergey Levine
3. Avi Singh
4. Benjamin Eysenbach
5. Suraj Nair
6. Julian Ibarz
7. Sudeep Dasari
8. Shagun Sodhani
9. Yash Chandak
10. Danny Driess

Papers from Annie Xie's perspective

Ordered by how strongly the researchers Annie Xie 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. 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning (2018) — 385 citations
• Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control (2018) — 474 citations
• Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight (2019) — 95 citations
• Few-Shot Goal Inference for Visuomotor Learning and Planning (2018) — 72 citations
• DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset (2024) — 905 citations
• Deep Reinforcement Learning amidst Lifelong Non-Stationarity (2020) — 73 citations
• Deep Reinforcement Learning amidst Continual Structured Non-Stationarity (2021) — 45 citations