Ruiqi Gao

According to our database, Ruiqi Gao authored at least 60 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SimVS: Simulating World Inconsistencies for Robust View Synthesis.

Alex Trevithick, Roni Paiss, Philipp Henzler, Dor Verbin, Rundi Wu, Hadi Alzayer, Ruiqi Gao, Ben Poole, Jonathan T. Barron, Aleksander Holynski, Ravi Ramamoorthi, Pratul P. Srinivasan

CoRR, 2024

CAT4D: Create Anything in 4D with Multi-View Video Diffusion Models.

Rundi Wu, Ruiqi Gao, Ben Poole, Alex Trevithick, Changxi Zheng, Jonathan T. Barron, Aleksander Holynski

CoRR, 2024

Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion.

Emiel Hoogeboom, Thomas Mensink, Jonathan Heek, Kay Lamerigts, Ruiqi Gao, Tim Salimans

CoRR, 2024

Think Twice Before You Act: Improving Inverse Problem Solving With MCMC.

Yaxuan Zhu, Zehao Dou, Haoxin Zheng, Yasi Zhang, Ying Nian Wu, Ruiqi Gao

CoRR, 2024

Generative Hierarchical Materials Search.

Sherry Yang, Simon L. Batzner, Ruiqi Gao, Muratahan Aykol, Alexander L. Gaunt, Brendan McMorrow, Danilo J. Rezende, Dale Schuurmans, Igor Mordatch, Ekin D. Cubuk

CoRR, 2024

Limited Out-of-Context Knowledge Reasoning in Large Language Models.

Peng Hu, Changjiang Gao, Ruiqi Gao, Jiajun Chen, Shujian Huang

CoRR, 2024

An Investigation of Conformal Isometry Hypothesis for Grid Cells.

Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu

CoRR, 2024

EM Distillation for One-step Diffusion Models.

Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao

CoRR, 2024

Latent Energy-Based Odyssey: Black-Box Optimization via Expanded Exploration in the Energy-Based Latent Space.

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

CoRR, 2024

CoLay: Controllable Layout Generation through Multi-conditional Latent Diffusion.

Chin-Yi Cheng, Ruiqi Gao, Forrest Huang, Yang Li

CoRR, 2024

CAT3D: Create Anything in 3D with Multi-View Diffusion Models.

Ruiqi Gao, Aleksander Holynski, Philipp Henzler, Arthur Brussee, Ricardo Martin-Brualla, Pratul P. Srinivasan, Jonathan T. Barron, Ben Poole

CoRR, 2024

MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space.

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

CoRR, 2024

Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood.

Yaxuan Zhu, Jianwen Xie, Ying Nian Wu, Ruiqi Gao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Large Language Models are Limited in Out-of-Context Knowledge Reasoning.

Peng Hu, Changjiang Gao, Ruiqi Gao, Jiajun Chen, Shujian Huang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

MagicMirror: Fast and High-Quality Avatar Generation with a Constrained Search Space.

Armand Comas Massague, Di Qiu, Menglei Chai, Marcel C. Bühler, Amit Raj, Ruiqi Gao, Qiangeng Xu, Mark Matthews, Paulo F. U. Gotardo, Sergio Orts-Escolano, Thabo Beeler

Proceedings of the Computer Vision - ECCV 2024, 2024

ReconFusion: 3D Reconstruction with Diffusion Priors.

Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Conformal Normalization in Recurrent Neural Network of Grid Cells.

Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu

CoRR, 2023

Understanding the Diffusion Objective as a Weighted Integral of ELBOs.

Diederik P. Kingma, Ruiqi Gao

CoRR, 2023

Learning Energy-Based Prior Model with Diffusion-Amortized MCMC.

Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian Ma, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation.

Diederik P. Kingma, Ruiqi Gao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Compiling Parallel Symbolic Execution with Continuations.

Guannan Wei, Songlin Jia, Ruiqi Gao, Haotian Deng, Shangyin Tan, Oliver Bracevac, Tiark Rompf

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

On Distillation of Guided Diffusion Models.

Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Weightings in Incremental ADCs: A Tutorial Review.

Ruiqi Gao, Mingqiang Guo, Sai-Weng Sin, Liang Qi, Biao Wang, Guoxing Wang, Rui Paulo Martins

Proceedings of the IEEE Custom Integrated Circuits Conference, 2023

2022

Deformable Generator Networks: Unsupervised Disentanglement of Appearance and Geometry.

Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis.

Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu

IEEE Trans. Pattern Anal. Mach. Intell., 2022

On Distillation of Guided Diffusion Models.

Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

CoRR, 2022

Imagen Video: High Definition Video Generation with Diffusion Models.

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

CoRR, 2022

Latent Diffusion Energy-Based Model for Interpretable Text Modeling.

Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu

CoRR, 2022

Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells.

Dehong Xu, Ruiqi Gao, Wenhao Zhang, Xue-Xin Wei, Ying Nian Wu

Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

Latent Diffusion Energy-Based Model for Interpretable Text Modelling.

Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu

Proceedings of the International Conference on Machine Learning, 2022

MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC.

Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion.

Ruiqi Gao, Jianwen Xie, Siyuan Huang, Yufan Ren, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Effective Learning of Descriptive and Generator Models and Learning Representations for Grid Cells and V1 Cells.

Ruiqi Gao

PhD thesis, 2021

On Path Integration of Grid Cells: Group Representation and Isotropic Scaling.

Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Theory of Label Propagation for Subpopulation Shift.

Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Energy-Based Models by Diffusion Recovery Likelihood.

Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesis.

Yaxuan Zhu, Ruiqi Gao, Siyuan Huang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Cooperative Training of Descriptor and Generator Networks.

Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu

IEEE Trans. Pattern Anal. Mach. Intell., 2020

A Representational Model of Grid Cells Based on Matrix Lie Algebras.

Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu

CoRR, 2020

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, Ying Nian Wu

CoRR, 2020

Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot.

Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Flow Contrastive Estimation of Energy-Based Models.

Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns.

Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Representation Learning: A Statistical Perspective.

Jianwen Xie, Ruiqi Gao, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

CoRR, 2019

Convergence of Adversarial Training in Overparametrized Networks.

Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee

CoRR, 2019

A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems.

Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang

CoRR, 2019

Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1.

Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu

CoRR, 2019

Convergence of Adversarial Training in Overparametrized Neural Networks.

Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multimodal 3D Convolutional Neural Networks for Classification of Brain Disease Using Structural MR and FDG-PET Images.

Kun Han, Haiwei Pan, Ruiqi Gao, Jieyao Yu, Bin Yang

Proceedings of the Data Science, 2019

Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion.

Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu

Proceedings of the 7th International Conference on Learning Representations, 2019

Unsupervised Disentangling of Appearance and Geometry by Deformable Generator Network.

Xianglei Xing, Tian Han, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Learning Dynamic Generator Model by Alternating Back-Propagation through Time.

Jianwen Xie, Ruiqi Gao, Zilong Zheng, Song-Chun Zhu, Ying Nian Wu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning Grid-like Units with Vector Representation of Self-Position and Matrix Representation of Self-Motion.

Ruiqi Gao, Jianwen Xie, Song-Chun Zhu, Ying Nian Wu

CoRR, 2018

A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models.

Ying Nian Wu, Ruiqi Gao, Tian Han, Song-Chun Zhu

CoRR, 2018

Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry.

Xianglei Xing, Ruiqi Gao, Tian Han, Song-Chun Zhu, Ying Nian Wu

CoRR, 2018

Learning Descriptor Networks for 3D Shape Synthesis and Analysis.

Jianwen Xie, Zilong Zheng, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning Generative ConvNets via Multi-Grid Modeling and Sampling.

Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching.

Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

Hong Song, Lei Chen, Ruiqi Gao, Iordachescu Ilie Mihaita Bogdan, Jian Yang, Shuliang Wang, Wentian Dong, Wenxiang Quan, Weimin Dang, Xin Yu

BMC Medical Informatics Decis. Mak., 2017

Learning Multi-grid Generative ConvNets by Minimal Contrastive Divergence.

Ruiqi Gao, Yang Lu, Junpei Zhou, Song-Chun Zhu, Ying Nian Wu

CoRR, 2017