Ruiqi Gao

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 64

Top Topics

Diffusion Models

Top Venues

Publications

Peiyu Yu, Dinghuai Zhang, Hengzhi He, Xiaojian Ma, Ruiyao Miao, Yifan Lu, Yasi Zhang, Deqian Kong, Ruiqi Gao, Jianwen Xie, Guang Cheng, Ying Nian Wu
Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space. CoRR (2024)
Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
EM Distillation for One-step Diffusion Models. CoRR (2024)
Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. ICLR (2024)
Chin-Yi Cheng, Ruiqi Gao, Forrest Huang, Yang Li
CoLay: Controllable Layout Generation through Multi-conditional Latent Diffusion. CoRR (2024)
Peng Hu, Changjiang Gao, Ruiqi Gao, Jiajun Chen, Shujian Huang
Limited Out-of-Context Knowledge Reasoning in Large Language Models. CoRR (2024)
Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, Ben Poole
CAT3D: Create Anything in 3D with Multi-View Diffusion Models. CoRR (2024)
Armand Comas Massague, Di Qiu, Menglei Chai, Marcel C. Bühler, Amit Raj, Ruiqi Gao, Qiangeng Xu, Mark Matthews, Paulo F. U. Gotardo, Octavia I. Camps, Sergio Orts-Escolano, Thabo Beeler
MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space. CoRR (2024)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
An Investigation of Conformal Isometry Hypothesis for Grid Cells. CoRR (2024)
Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. CoRR (2023)
Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski
ReconFusion: 3D Reconstruction with Diffusion Priors. CoRR (2023)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Normalization in Recurrent Neural Network of Grid Cells. CoRR (2023)
Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Learning Energy-Based Prior Model with Diffusion-Amortized MCMC. NeurIPS (2023)
Guannan Wei, Songlin Jia, Ruiqi Gao, Haotian Deng, Shangyin Tan, Oliver Bracevac, Tiark Rompf
Compiling Parallel Symbolic Execution with Continuations. ICSE (2023)
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
On Distillation of Guided Diffusion Models. CVPR (2023)
Ruiqi Gao, Mingqiang Guo, Sai-Weng Sin, Liang Qi, Biao Wang, Guoxing Wang, Rui Paulo Martins
Weightings in Incremental ADCs: A Tutorial Review. CICC (2023)
Diederik P. Kingma, Ruiqi Gao
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation. NeurIPS (2023)
Diederik P. Kingma, Ruiqi Gao
Understanding the Diffusion Objective as a Weighted Integral of ELBOs. CoRR (2023)
Yaxuan Zhu, Jianwen Xie, Yingnian Wu, Ruiqi Gao
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood. CoRR (2023)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. NeurReps (2022)
Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu
Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion. AAAI (2022)
Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry. IEEE Trans. Pattern Anal. Mach. Intell. 44 (3) (2022)
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans
Imagen Video: High Definition Video Generation with Diffusion Models. CoRR (2022)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
Latent Diffusion Energy-Based Model for Interpretable Text Modelling. ICML (2022)
Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu
Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. CoRR (2022)
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
Latent Diffusion Energy-Based Model for Interpretable Text Modeling. CoRR (2022)
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. ICLR (2022)
Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
On Distillation of Guided Diffusion Models. CoRR (2022)
Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 44 (5) (2022)
Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei
A Theory of Label Propagation for Subpopulation Shift. CoRR (2021)
Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling. NeurIPS (2021)
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
Learning Energy-Based Models by Diffusion Recovery Likelihood. ICLR (2021)
Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei
A Theory of Label Propagation for Subpopulation Shift. ICML (2021)
Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu
Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis. CVPR (2021)
Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Yingnian Wu
Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis. CoRR (2021)
Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis. CoRR (2020)
Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. CoRR (2020)
Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
A Representational Model of Grid Cells Based on Matrix Lie Algebras. CoRR (2020)
Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. NeurIPS (2020)
Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
Flow Contrastive Estimation of Energy-Based Models. CVPR (2020)
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
Learning Energy-Based Models by Diffusion Recovery Likelihood. CoRR (2020)
Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu
Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC. CoRR (2020)
Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. AAAI (2020)
Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Cooperative Training of Descriptor and Generator Networks. IEEE Trans. Pattern Anal. Mach. Intell. 42 (1) (2020)
Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu
Flow Contrastive Estimation of Energy-Based Models. CoRR (2019)
Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns. CoRR (2019)
Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang
A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems. CoRR (2019)
Kun Han, Haiwei Pan, Ruiqi Gao, Jieyao Yu, Bin Yang
Multimodal 3D Convolutional Neural Networks for Classification of Brain Disease Using Structural MR and FDG-PET Images. ICPCSEE (1) (2019)
Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee
Convergence of Adversarial Training in Overparametrized Networks. CoRR (2019)
Xianglei Xing, Tian Han, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network. CVPR (2019)
Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee
Convergence of Adversarial Training in Overparametrized Neural Networks. NeurIPS (2019)
Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu
Representation Learning: A Statistical Perspective. CoRR (2019)
Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion. ICLR (Poster) (2019)
Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
Learning Dynamic Generator Model by Alternating Back-Propagation through Time. AAAI (2019)
Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1. CoRR (2019)
Ying Nian Wu, Ruiqi Gao, Tian Han, Song-Chun Zhu
A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models. CoRR (2018)
Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CVPR (2018)
Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu
Learning Dynamic Generator Model by Alternating Back-Propagation Through Time. CoRR (2018)
Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu
Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry. CoRR (2018)
Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu
Learning Generative ConvNets via Multi-Grid Modeling and Sampling. CVPR (2018)
Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu
Learning Descriptor Networks for 3D Shape Synthesis and Analysis. CoRR (2018)
Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu
Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching. AAAI (2018)
Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion. CoRR (2018)
Hong Song, Lei Chen, Ruiqi Gao, Iordachescu Ilie Mihaita Bogdan, Jian Yang, Shuliang Wang, Wentian Dong, Wenxiang Quan, Weimin Dang, Xin Yu
Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM. BMC Medical Informatics Decis. Mak. 17 (S-3) (2017)
Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu
Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence. CoRR (2017)