Bo Liu

Artificial Intelligence · Neural Information Processing Systems · 2020–2023

A researcher in the Science corpus: 7 papers; trusts 330 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 245 citations into it
• Computer Vision and Pattern Recognition — 137 citations into it; #19,788 of 21,575 by trust here, #9,435 by citations
• Reinforcement Learning — 42 citations into it; #2,099 of 2,242 by trust here, #2,160 by citations
• Privacy & Security — 39 citations into it
• Safety, Robustness & Interpretability — 35 citations into it
• Representation & Self-Supervised Learning — 30 citations into it
• Meta & Continual Learning — 29 citations into it
• Optimization & Training — 25 citations into it

Whom Bo Liu trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Yann LeCun
6. Kaiming He
7. Radford M. Neal
8. Ilya Sutskever
9. Marc'Aurelio Ranzato
10. Jimmy Ba

Who trusts Bo Liu overall

1. Liangzu Peng
2. Namhoon Cho
3. Lin Guan
4. Theodore R. Sumers
5. Qian Liu
6. Paris V. Giampouras
7. Youngjae Min
8. Mary Anne Smart
9. Shunyu Yao

Papers from Bo Liu's perspective

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

Their papers

• A Lifelong Learning Approach to Mobile Robot Navigation (2021) — 118 citations
• LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning (2023) — 1,206 citations
• LLM+P: Empowering Large Language Models with Optimal Planning Proficiency (2023) — 653 citations
• When Machine Learning Meets Privacy (2020) — 350 citations
• Continual Learning and Private Unlearning (2022) — 152 citations
• Conflict-Averse Gradient Descent for Multi-task Learning (2021) — 602 citations
• Lifelong Navigation (2020) — 10 citations