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Jiaming Song
Jiaming Song
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
Denoising diffusion implicit models
J Song, C Meng, S Ermon
International Conference on Learning Representations (ICLR) 2021, 2020
53902020
Sdedit: Guided image synthesis and editing with stochastic differential equations
C Meng, Y He, Y Song, J Song, J Wu, JY Zhu, S Ermon
arXiv preprint arXiv:2108.01073, 2021
14262021
Infovae: Balancing learning and inference in variational autoencoders
S Zhao, J Song, S Ermon
Proceedings of the aaai conference on artificial intelligence 33 (01), 5885-5892, 2019
818*2019
Denoising diffusion restoration models
B Kawar, M Elad, S Ermon, J Song
Advances in Neural Information Processing Systems 35, 23593-23606, 2022
6732022
ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Y Balaji, S Nah, X Huang, A Vahdat, J Song, Q Zhang, K Kreis, M Aittala, ...
arXiv preprint arXiv:2211.01324, 2022
6452022
Proceedings of the 26th International Joint Conference on Artificial Intelligence
C Sierra
AAAI Press, 2017
5772017
Infogail: Interpretable imitation learning from visual demonstrations
Y Li, J Song, S Ermon
Advances in neural information processing systems 30, 2017
4822017
Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Y Tashiro, J Song, Y Song, S Ermon
Advances in Neural Information Processing Systems 34, 24804-24816, 2021
4322021
Multi-agent generative adversarial imitation learning
J Song, H Ren, D Sadigh, S Ermon
Neural Information Processing Systems (NeurIPS) 2018, 2018
2742018
Permutation invariant graph generation via score-based generative modeling
C Niu, Y Song, J Song, S Zhao, A Grover, S Ermon
International Conference on Artificial Intelligence and Statistics, 4474-4484, 2020
2282020
Understanding the limitations of variational mutual information estimators
J Song, S Ermon
International Conference on Learning Representations (ICLR) 2020, 2019
2172019
Learning controllable fair representations
J Song, P Kalluri, A Grover, S Zhao, S Ermon
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
2082019
Towards deeper understanding of variational autoencoding models
S Zhao, J Song, S Ermon
arXiv preprint arXiv:1702.08658, 2017
2022017
Pseudoinverse-guided diffusion models for inverse problems
J Song, A Vahdat, M Mardani, J Kautz
International Conference on Learning Representations, 2023
1972023
Physdiff: Physics-guided human motion diffusion model
Y Yuan, J Song, U Iqbal, A Vahdat, J Kautz
Proceedings of the IEEE/CVF international conference on computer vision …, 2023
1932023
Dual diffusion implicit bridges for image-to-image translation
X Su, J Song, C Meng, S Ermon
arXiv preprint arXiv:2203.08382, 2022
1822022
Learning hierarchical features from deep generative models
S Zhao, J Song, S Ermon
International Conference on Machine Learning, 4091-4099, 2017
173*2017
Iq-learn: Inverse soft-q learning for imitation
D Garg, S Chakraborty, C Cundy, J Song, S Ermon
Advances in Neural Information Processing Systems 34, 4028-4039, 2021
1612021
A theory of usable information under computational constraints
Y Xu, S Zhao, J Song, R Stewart, S Ermon
nternational Conference on Learning Representations (ICLR) 2020, 2020
1552020
Bias and generalization in deep generative models: An empirical study
S Zhao, H Ren, A Yuan, J Song, N Goodman, S Ermon
Neural Information Processing Systems (NeurIPS) 2018, 2018
1552018
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Articles 1–20