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RUIQI GAO
RUIQI GAO
Research Scientist, Google DeepMind
Geverifieerd e-mailadres voor google.com - Homepage
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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
9192022
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
2662023
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
1602018
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
1522018
Learning Energy-Based Models by Diffusion Recovery Likelihood
R Gao, Y Song, B Poole, YN Wu, DP Kingma
arXiv preprint arXiv:2012.08125, 2020
1142020
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
1102020
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
892018
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
832018
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
632022
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
482020
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
412018
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
392019
Understanding diffusion objectives as the ELBO with simple data augmentation
D Kingma, R Gao
Advances in Neural Information Processing Systems 36, 2024
332024
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
332019
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
322020
ReconFusion: 3D Reconstruction with Diffusion Priors
R Wu, B Mildenhall, P Henzler, K Park, R Gao, D Watson, PP Srinivasan, ...
arXiv preprint arXiv:2312.02981, 2023
262023
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
212022
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
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
212019
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
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Artikelen 1–20