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RUIQI GAO
RUIQI GAO
Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Imagen Video: High Definition Video Generation with Diffusion Models
J Ho, W Chan, C Saharia, J Whang, R Gao, A Gritsenko, DP Kingma, ...
arXiv preprint arXiv:2210.02303, 2022
6712022
On distillation of guided diffusion models
C Meng, R Rombach, R Gao, D Kingma, S Ermon, J Ho, T Salimans
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
1962023
Learning Descriptor Networks for 3D Shape Synthesis and Analysis
J Xie, Z Zheng, R Gao, W Wang, SC Zhu, YN Wu
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
1532018
Cooperative training of descriptor and generator networks
J Xie, Y Lu, R Gao, SC Zhu, YN Wu
IEEE transactions on pattern analysis and machine intelligence 42 (1), 27-45, 2018
1462018
Learning Energy-Based Models by Diffusion Recovery Likelihood
R Gao, Y Song, B Poole, YN Wu, DP Kingma
arXiv preprint arXiv:2012.08125, 2020
1022020
Flow contrastive estimation of energy-based models
R Gao, E Nijkamp, DP Kingma, Z Xu, AM Dai, YN Wu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
952020
Learning generative convnets via multi-grid modeling and sampling
R Gao, Y Lu, J Zhou, SC Zhu, YN Wu
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
822018
Cooperative learning of energy-based model and latent variable model via mcmc teaching
J Xie, Y Lu, R Gao, YN Wu
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
812018
Generative VoxelNet: learning energy-based models for 3D shape synthesis and analysis
J Xie, Z Zheng, R Gao, W Wang, SC Zhu, YN Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (5), 2468-2484, 2020
452020
Latent diffusion energy-based model for interpretable text modeling
P Yu, S Xie, X Ma, B Jia, B Pang, R Gao, Y Zhu, SC Zhu, YN Wu
arXiv preprint arXiv:2206.05895, 2022
432022
Learning grid cells as vector representation of self-position coupled with matrix representation of self-motion
R Gao, J Xie, SC Zhu, YN Wu
arXiv preprint arXiv:1810.05597, 2018
392018
Learning dynamic generator model by alternating back-propagation through time
J Xie, R Gao, Z Zheng, SC Zhu, YN Wu
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5498-5507, 2019
382019
Unsupervised disentangling of appearance and geometry by deformable generator network
X Xing, T Han, R Gao, SC Zhu, YN Wu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
322019
Deformable generator networks: unsupervised disentanglement of appearance and geometry
X Xing, R Gao, T Han, SC Zhu, YN Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1162-1179, 2020
312020
Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC
E Nijkamp, R Gao, P Sountsov, S Vasudevan, B Pang, SC Zhu, YN Wu
arXiv preprint arXiv:2006.06897, 2020
212020
MCMC should mix: learning energy-based model with neural transport latent space MCMC.
E Nijkamp, R Gao, P Sountsov, S Vasudevan, B Pang, SC Zhu, YN Wu
International Conference on Learning Representations (ICLR 2022)., 2022
202022
A tale of three probabilistic families: Discriminative, descriptive, and generative models
YN Wu, R Gao, T Han, SC Zhu
Quarterly of Applied Mathematics 77 (2), 423-465, 2019
202019
A remark on copy number variation detection methods
S Li, X Dou, R Gao, X Ge, M Qian, L Wan
PloS one 13 (4), e0196226, 2018
192018
Representation learning: A statistical perspective
J Xie, R Gao, E Nijkamp, SC Zhu, YN Wu
Annual Review of Statistics and Its Application 7, 303-335, 2020
162020
Motion-based generator model: Unsupervised disentanglement of appearance, trackable and intrackable motions in dynamic patterns
J Xie, R Gao, Z Zheng, SC Zhu, YN Wu
Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12442 …, 2020
152020
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