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Jiaming Song
Jiaming Song
Stanford University
Подтвержден адрес электронной почты в домене cs.stanford.edu - Главная страница
Название
Процитировано
Процитировано
Год
Denoising diffusion implicit models
J Song, C Meng, S Ermon
International Conference on Learning Representations (ICLR) 2021, 2020
71102020
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
17212021
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
13932022
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
874*2019
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA
SP Singh, S Markovitch
AAAI press, 2017
834*2017
Denoising diffusion restoration models
B Kawar, M Elad, S Ermon, J Song
Advances in Neural Information Processing Systems 35, 23593-23606, 2022
8212022
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
7532022
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
5522021
Infogail: Interpretable imitation learning from visual demonstrations
Y Li, J Song, S Ermon
Advances in neural information processing systems 30, 2017
5062017
Multi-agent generative adversarial imitation learning
J Song, H Ren, D Sadigh, S Ermon
Neural Information Processing Systems (NeurIPS) 2018, 2018
2912018
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
2712020
Pseudoinverse-guided diffusion models for inverse problems
J Song, A Vahdat, M Mardani, J Kautz
International Conference on Learning Representations, 2023
2612023
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
2412023
Understanding the limitations of variational mutual information estimators
J Song, S Ermon
International Conference on Learning Representations (ICLR) 2020, 2019
2392019
Learning controllable fair representations
J Song, P Kalluri, A Grover, S Zhao, S Ermon
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
2162019
Towards deeper understanding of variational autoencoding models
S Zhao, J Song, S Ermon
arXiv preprint arXiv:1702.08658, 2017
2132017
Dual diffusion implicit bridges for image-to-image translation
X Su, J Song, C Meng, S Ermon
arXiv preprint arXiv:2203.08382, 2022
2102022
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
2032021
Learning hierarchical features from deep generative models
S Zhao, J Song, S Ermon
International Conference on Machine Learning, 4091-4099, 2017
177*2017
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
1712020
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Статьи 1–20