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Jiaming Song
Jiaming Song
Dirección de correo verificada de cs.stanford.edu - Página principal
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Citado por
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Año
Denoising diffusion implicit models
J Song, C Meng, S Ermon
International Conference on Learning Representations (ICLR) 2021, 2020
25592020
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
7812021
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
717*2019
Infogail: Interpretable imitation learning from visual demonstrations
Y Li, J Song, S Ermon
Advances in neural information processing systems 30, 2017
4712017
Denoising diffusion restoration models
B Kawar, M Elad, S Ermon, J Song
Advances in Neural Information Processing Systems 35, 23593-23606, 2022
3632022
ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Y Balaji, S Nah, X Huang, A Vahdat, J Song, K Kreis, M Aittala, T Aila, ...
arXiv preprint arXiv:2211.01324, 2022
3572022
Multi-agent generative adversarial imitation learning
J Song, H Ren, D Sadigh, S Ermon
Neural Information Processing Systems (NeurIPS) 2018, 2018
2382018
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
2312021
Towards deeper understanding of variational autoencoding models
S Zhao, J Song, S Ermon
arXiv preprint arXiv:1702.08658, 2017
1902017
Understanding the limitations of variational mutual information estimators
J Song, S Ermon
International Conference on Learning Representations (ICLR) 2020, 2019
1822019
Learning controllable fair representations
J Song, P Kalluri, A Grover, S Zhao, S Ermon
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
1772019
Learning hierarchical features from deep generative models
S Zhao, J Song, S Ermon
International Conference on Machine Learning, 4091-4099, 2017
161*2017
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
1452020
Bias correction of learned generative models using likelihood-free importance weighting
A Grover, J Song, A Agarwal, K Tran, A Kapoor, E Horvitz, S Ermon
Neural Information Processing Systems (NeurIPS) 2019, 2019
1272019
A-nice-mc: Adversarial training for mcmc
J Song, S Zhao, S Ermon
Neural Information Processing Systems (NeurIPS) 2017, 2017
1252017
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
1202020
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
1192018
Multi-agent adversarial inverse reinforcement learning
L Yu, J Song, S Ermon
International Conference on Machine Learning, 7194-7201, 2019
1182019
Max-margin nonparametric latent feature models for link prediction
J Zhu, J Song, B Chen
arXiv preprint arXiv:1602.07428, 2016
1112016
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
1022021
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Artículos 1–20