Jiajun Wu

Massachusetts Institute of Technology, Stanford University, Google (United States), Institute of Occupational Medicine, Ministry of Education, Shanghai University, Guangdong University of Technology, Jianghan University

论文数

57

总引用数

2,079

H-Index

22

关于

暂无简介。

研究焦点

Artificial intelligence55 · 2,063 次引用
Computer science55 · 2,063 次引用
Robot41 · 1,155 次引用
Human–computer interaction25 · 947 次引用
Computer graphics (images)14 · 865 次引用
Computer vision26 · 859 次引用
Representation (politics)12 · 707 次引用
Simulation12 · 593 次引用
Physics engine6 · 456 次引用
Robotics13 · 451 次引用
Mathematics14 · 429 次引用
Set (abstract data type)7 · 416 次引用

主要成就

22
H 指数
57
论文
2,079
总引用数
36
篇均引用
🏆 最高被引论文
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
223 次引用 · 2019
📈 最高产年份: 2023 (15 论文)
🤝 主要合作者: 357
🏛 所属机构: Massachusetts Institute of Technology, Stanford University, Google (United States), Institute of Occupational Medicine, Ministry of Education, Shanghai University

代表论文

  1. 1
    ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
    223 次引用 · 2019
  2. 2
    Neural Radiance Flow for 4D View Synthesis and Video Processing
    209 次引用 · 2021
  3. 3
    See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion
    124 次引用 · 2019
  4. 4
    Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration<sup>0</sup>
    119 次引用 · 2024
  5. 5
    3D Shape Perception from Monocular Vision, Touch, and Shape Priors
    118 次引用 · 2018
  6. 6
    DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
    108 次引用 · 2024
  7. 7
    Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
    107 次引用 · 2018
  8. 8
    Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
    95 次引用 · 2018
  9. 9
    Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
    88 次引用 · 2018
  10. 10
    DensePhysNet: Learning Dense Physical Object Representations Via Multi-Step Dynamic Interactions
    87 次引用 · 2019

主要合作者

JBJoshua B. Tenenbaum18 篇合著论文RGRuohan Gao7 篇合著论文JBJeannette Bohg6 篇合著论文SSShuran Song6 篇合著论文YLYunzhu Li6 篇合著论文STStephen Tian6 篇合著论文CFChelsea Finn5 篇合著论文DSDorsa Sadigh5 篇合著论文ARAlberto Rodríguez5 篇合著论文RMRoberto Martín-Martín4 篇合著论文LFLi Fei-Fei4 篇合著论文MBMaria Bauzá4 篇合著论文JGJensen Gao4 篇合著论文WYWenzhen Yuan4 篇合著论文NFNima Fazeli4 篇合著论文WTWilliam T. Freeman4 篇合著论文ZXZhenjia Xu4 篇合著论文HWHomer Walke4 篇合著论文KHKyle Hsu4 篇合著论文CAChristopher Agia4 篇合著论文
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