Josiah Wong
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 4 papers; trusts 27 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 117 citations into it; #16,805 of 35,345 by trust here, #14,718 by citations
- Reinforcement Learning — 97 citations into it
- Control and Systems Engineering — 69 citations into it; #3,284 of 8,257 by trust here, #1,875 by citations
- Computer Vision and Pattern Recognition — 59 citations into it
- Robotics & Control — 51 citations into it; #230 of 609 by trust here, #208 by citations
- Mechanical Engineering — 17 citations into it; #2,539 of 8,300 by trust here, #3,848 by citations
- Computational Theory and Mathematics — 9 citations into it
Whom Josiah Wong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Diederik P. Kingma
- E. Todorov
- Geoffrey E. Hinton
- Sergey Levine
- Andrew Barto
- Kaiming He
- Alex Krizhevsky
- Yuke Zhu
- Yoshua Bengio
Who trusts Josiah Wong overall
- Ajay Mandlekar
- Linxi (Jim) Fan
- Soroush Nasiriany
- Yuke Zhu
- Bo Liu
- Yunfan Jiang
- Danfei Xu
- Shangding Gu
- Yizhou Huang
- Youngwoon Lee
Papers from Josiah Wong's perspective
Ordered by how strongly the researchers Josiah Wong trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- GENERATIVE ADVERSARIAL NETS
Their papers
- robosuite: A Modular Simulation Framework and Benchmark for Robot Learning (2020) — 702 citations
- Learning Multi-Arm Manipulation Through Collaborative Teleoperation (2020) — 58 citations
- BEHAVIOR-1K: A Benchmark for Embodied AI with 1, 000 Everyday Activities and Realistic Simulation (2022) — 370 citations
- What Matters in Learning from Offline Human Demonstrations for Robot Manipulation (2021) — 937 citations