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Yang Song
Yang Song
OpenAI
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Titel
Zitiert von
Zitiert von
Jahr
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
11562*2023
Score-Based Generative Modeling through Stochastic Differential Equations
Y Song, J Sohl-Dickstein, DP Kingma, A Kumar, S Ermon, B Poole
International Conference on Learning Representations, 2021
64092021
Generative modeling by estimating gradients of the data distribution
Y Song, S Ermon
Advances in Neural Information Processing Systems, 11918-11930, 2019
40942019
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
C Meng, Y He, Y Song, J Song, J Wu, JY Zhu, S Ermon
International Conference on Learning Representations, 2021
1744*2021
Diffusion models: A comprehensive survey of methods and applications
L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, W Zhang, B Cui, ...
ACM Computing Surveys, 2022
17112022
Improved techniques for training score-based generative models
Y Song, S Ermon
Advances in Neural Information Processing Systems 33, 2020
11842020
Pixeldefend: Leveraging generative models to understand and defend against adversarial examples
Y Song, T Kim, S Nowozin, S Ermon, N Kushman
International Conference on Learning Representations, 2018
9992018
Consistency Models
Y Song, P Dhariwal, M Chen, I Sutskever
arXiv preprint arXiv:2303.01469, 2023
9332023
Maximum Likelihood Training of Score-Based Diffusion Models
Y Song, C Durkan, I Murray, S Ermon
arXiv preprint arXiv:2101.09258, 2021
6552021
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
M Xu, L Yu, Y Song, C Shi, S Ermon, J Tang
International Conference on Learning Representations, 2021
5982021
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
5592021
Solving Inverse Problems in Medical Imaging with Score-Based Generative Models
Y Song, L Shen, L Xing, S Ermon
arXiv preprint arXiv:2111.08005, 2021
5592021
Sliced score matching: A scalable approach to density and score estimation
Y Song, S Garg, J Shi, S Ermon
Uncertainty in Artificial Intelligence, 574-584, 2019
4992019
Efficient graph generation with graph recurrent attention networks
R Liao, Y Li, Y Song, S Wang, W Hamilton, DK Duvenaud, R Urtasun, ...
Advances in Neural Information Processing Systems, 4255-4265, 2019
3962019
Constructing Unrestricted Adversarial Examples with Generative Models
Y Song, R Shu, N Kushman, S Ermon
Advances in Neural Information Processing Systems, 8322-8333, 2018
3592018
How to Train Your Energy-Based Models
Y Song, DP Kingma
arXiv preprint arXiv:2101.03288, 2021
3112021
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
2722020
Learning Energy-Based Models by Diffusion Recovery Likelihood
R Gao, Y Song, B Poole, YN Wu, DP Kingma
International Conference on Learning Representations, 2020
1392020
Improved Techniques for Training Consistency Models
Y Song, P Dhariwal
arXiv preprint arXiv:2310.14189, 2023
1352023
Training deep neural networks via direct loss minimization
Y Song, A Schwing, R Zemel, R Urtasun
International Conference on Machine Learning, 2169-2177, 2016
1282016
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