Yang Song (宋飏)
Yang Song (宋飏)
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
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
3422018
Constructing Unrestricted Adversarial Examples with Generative Models
Y Song, R Shu, N Kushman, S Ermon
Advances in Neural Information Processing Systems, 8322-8333, 2018
102*2018
Generative modeling by estimating gradients of the data distribution
Y Song, S Ermon
Advances in Neural Information Processing Systems, 11918-11930, 2019
612019
Training deep neural networks via direct loss minimization
Y Song, A Schwing, R Zemel, R Urtasun
International Conference on Machine Learning, 2169-2177, 2016
56*2016
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
342019
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
212019
Stochastic gradient geodesic mcmc methods
C Liu, J Zhu, Y Song
Advances in neural information processing systems 29, 3009-3017, 2016
212016
Mintnet: Building invertible neural networks with masked convolutions
Y Song, C Meng, S Ermon
Advances in Neural Information Processing Systems, 11004-11014, 2019
122019
Bayesian matrix completion via adaptive relaxed spectral regularization
Y Song, J Zhu
Thirtieth AAAI Conference on Artificial Intelligence, 2016
102016
Improved techniques for training score-based generative models
Y Song, S Ermon
Advances in Neural Information Processing Systems 33, 2020
82020
Unsupervised Out-of-Distribution Detection with Batch Normalization
J Song, Y Song, S Ermon
arXiv preprint arXiv:1910.09115, 2019
82019
Diversity can be Transferred: Output Diversification for White-and Black-box Attacks
Y Tashiro, Y Song, S Ermon
Advances in Neural Information Processing Systems 33, 2020
7*2020
Accelerating Natural Gradient with Higher-Order Invariance
Y Song, J Song, S Ermon
International Conference on Machine Learning, 2018
72018
Training Deep Energy-Based Models with f-Divergence Minimization
L Yu, Y Song, J Song, S Ermon
arXiv preprint arXiv:2003.03463, 2020
62020
Gaussianization Flows
C Meng, Y Song, J Song, S Ermon
arXiv preprint arXiv:2003.01941, 2020
62020
Kernel Bayesian Inference with posterior regularization
Y Song, J Zhu, Y Ren
Advances in Neural Information Processing Systems 29, 4763-4771, 2016
62016
Permutation Invariant Graph Generation via Score-Based Generative Modeling
C Niu, Y Song, J Song, S Zhao, A Grover, S Ermon
arXiv preprint arXiv:2003.00638, 2020
12020
Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation
Y Song, C Meng, R Liao, S Ermon
arXiv preprint arXiv:2002.03629, 2020
12020
Efficient learning of generative models via finite-difference score matching
T Pang, T Xu, C Li, Y Song, S Ermon, J Zhu
Advances in Neural Information Processing Systems 33, 2020
12020
Imitation with Neural Density Models
K Kim, A Jindal, Y Song, J Song, Y Sui, S Ermon
arXiv preprint arXiv:2010.09808, 2020
2020
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Articles 1–20