Yang Song

Orcid: 0000-0003-3193-1679

Affiliations:
  • Stanford University, CA, USA


According to our database1, Yang Song authored at least 48 papers between 2015 and 2024.

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Bibliography

2024
Diffusion Models: A Comprehensive Survey of Methods and Applications.
ACM Comput. Surv., April, 2024

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing.
CoRR, 2024

2022
Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training.
CoRR, 2022

Diffusion Models: A Comprehensive Survey of Methods and Applications.
CoRR, 2022

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Solving Inverse Problems in Medical Imaging with Score-Based Generative Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Density Ratio Estimation via Infinitesimal Classification.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations.
CoRR, 2021

On Maximum Likelihood Training of Score-Based Generative Models.
CoRR, 2021

How to Train Your Energy-Based Models.
CoRR, 2021

Pseudo-Spherical Contrastive Divergence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Maximum Likelihood Training of Score-Based Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Estimating High Order Gradients of the Data Distribution by Denoising.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Imitation with Neural Density Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving.
Proceedings of the 38th International Conference on Machine Learning, 2021

Anytime Sampling for Autoregressive Models via Ordered Autoencoding.
Proceedings of the 9th International Conference on Learning Representations, 2021

Improved Autoregressive Modeling with Distribution Smoothing.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Energy-Based Models by Diffusion Recovery Likelihood.
Proceedings of the 9th International Conference on Learning Representations, 2021

Score-Based Generative Modeling through Stochastic Differential Equations.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Understanding Classifier Mistakes with Generative Models.
CoRR, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
CoRR, 2020

Output Diversified Initialization for Adversarial Attacks.
CoRR, 2020

Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation.
CoRR, 2020

Diversity can be Transferred: Output Diversification for White- and Black-box Attacks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Learning of Generative Models via Finite-Difference Score Matching.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Autoregressive Score Matching.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improved Techniques for Training Score-Based Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Training Deep Energy-Based Models with f-Divergence Minimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Permutation Invariant Graph Generation via Score-Based Generative Modeling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Gaussianization Flows.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Unsupervised Out-of-Distribution Detection with Batch Normalization.
CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.
CoRR, 2019

Sliced Score Matching: A Scalable Approach to Density and Score Estimation.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

MintNet: Building Invertible Neural Networks with Masked Convolutions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generative Modeling by Estimating Gradients of the Data Distribution.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Generative Adversarial Examples.
CoRR, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
CoRR, 2018

Constructing Unrestricted Adversarial Examples with Generative Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Accelerating Natural Gradient with Higher-Order Invariance.
Proceedings of the 35th International Conference on Machine Learning, 2018

PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

2016
Kernel Bayesian Inference with Posterior Regularization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Stochastic Gradient Geodesic MCMC Methods.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Training Deep Neural Networks via Direct Loss Minimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Direct Loss Minimization for Training Deep Neural Nets.
CoRR, 2015


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