Publications

(*) denotes equal contribution.

2021

  1. AAAI
    Learning Vector Representation of Local Content and Matrix Representation of Local Motion, with Implications for V1
    Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, and Ying Nian Wu
    The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022
  2. NeurIPS
    On Path Integration of Grid Cells: Group Representation and Isotropic Scaling
    Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, and Ying Nian Wu
    The 35th Conference on Neural Information Processing Systems, 2021
  3. CVPR
    Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis
    Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, and Ying Nian Wu
    Conference on Computer Vision and Pattern Recognition (CVPR), 2021
  4. ICLR
    Learning Energy­-Based Models by Diffusion Recovery Likelihood
    Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, and Diederik P. Kingma
    Ninth International Conference of Learning Representations (ICLR), 2021
  5. 2020

    1. arXiv
      Learning Energy-based Model with Flow-Based Backbone by Neural Transport MCMC
      Erik Nijkamp*, Ruiqi Gao*, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, and Ying Nian Wu
      arXiv preprint: 2006.06897, 2020
    2. CVPR Oral
      Flow Contrastive Estimation of Energy­-Based Models
      Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, and Ying Nian Wu
      Conference on Computer Vision and Pattern Recognition (CVPR), 2020
      NeurIPS workshop on Bayesian Deep Learning, 2019
    3. AAAI Oral
      Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns
      Jianwen Xie*, Ruiqi Gao*, Zilong Zheng, Song-Chun Zhu, and Ying Nian Wu
      The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020

    2019

    1. Journal
      Representation Learning: A Statistical Perspective
      Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, and Ying Nian Wu
      Annual Review of Statistics and Its Application (ARSIA), 2020
    2. ICLR
      Learning Grid Cells as Vector Representation of Self­-Position Coupled with Matrix Representation of Self­-Motion
      Ruiqi Gao*, Jianwen Xie*, Song-Chun Zhu, and Ying Nian Wu
      Seventh International Conference on Learning Representations (ICLR), 2019
    3. AAAI
      Learning Dynamic Generator Model by Alternating Back­-Propagation Through Time
      Jianwen Xie*, Ruiqi Gao*, Zilong Zheng, Song-Chun Zhu, and Ying Nian Wu
      The Thirty­-Third AAAI Conference on Artificial Intelligence (AAAI), 2019
    4. CVPR TPAMI
      Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry
      Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, and Ying Nian Wu
      Conference on Computer Vision and Pattern Recognition (CVPR), 2019
      IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
    5. Journal
      A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
      Ying Nian Wu, Ruiqi Gao, Tian Han, and Song-Chun Zhu
      Quarterly of Applied Mathematics (QAM), 2019

    2018

    1. CVPR Spotlight
      Learning Energy­-Based Models as Generative ConvNets via Multi­-grid Modeling and Sampling
      Ruiqi Gao*, Yang Lu*, Junpei Zhou, Song-Chun Zhu, and Ying Nian Wu
      Conference on Computer Vision and Pattern Recognition (CVPR), 2018
    2. AAAI Oral TPAMI
      Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching
      Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, and Ying Nian Wu
      The Thirty­-Second AAAI Conference on Artificial Intelligence (AAAI), 2018
      IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
    3. CVPR Oral
      Learning Descriptor Networks for 3D Shape Synthesis and Analysis
      Jianwen Xie*, Zilong Zheng*, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, and Ying Nian Wu
      Conference on Computer Vision and Pattern Recognition (CVPR), 2018

    2017

    1. Journal
      Exploring Generative Perspective of Convolutional Neural Networks by Learning Random Field Models
      Yang Lu, Ruiqi Gao, Song-Chun Zhu, and Ying Nian Wu
      Statistics and Its Interface, 2017
    2. Journal
      Correspondence of D. melanogaster and C. elegans developmental stages revealed by alternative splicing dynamics of conserved exon
      Ruiqi Gao, and Jingyi Jessica Li
      BMC Genomics, 2017