Slide 79
Slide 79 text
参考⽂献
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1. J. Behrmann, W. Grathwohl, R. T. Q. Chen, D. Duvenaud, J-H. Jacobsen. Invertible Residual
Networks. ICML 2019.
2. R. T. Q. Chen, J. Behrmann, D. Duvenaud, J-H. Jacobsen. Residual Flows for Invertible
Generative Modeling. ICML 2019.
3. R. T. Q. Chen, Y. Rubanova, J. Bettencourt and D. Duvenaud. Neural Ordinary Differential
Equations. NIPS 2018.
4. L. Dinh, D. Krueger and Y. Bengio. Non-linear Independent Components Estimation. ICLR 2015.
5. L. Dinh, J. Sohl-Dickstein and S. Bengio. Density estimation using Real NVP. ICLR 2017.
6. W. Grathwohl, R. T. Q. Chen, J. Bettencourt, I. Sutskever and D. Duvenaud. FFJORD: Free-
form Continuous Dynamics for Scalable Reversible Generative Models. ICLR 2019.
7. J. Ho, X. Chen, A. Srinivas, Y. Duan, P. Abbeel. Flow++: Improving Flow-Based Generative
Models with Variational Dequantization and Architecture Design. ICML 2019.
8. D. P. Kingma, P. Dhariwal. Glow: Generative Flow with Invertible 1×1 Convolutions. NIPS 2018.
9. I. Kobyzev, S. Prince and M. A. Brubaker. Normalizing Flows: Introduction and Ideas.
arXiv2019.
10. M. Kumar, M. Babaeizadeh, D. Erhan, C. Finn, S. Levine, L. Dinh and D. Kingma. VideoFlow: A
Flow-Based Generative Model for Video. ICML 2019.
11. R. Liu, Y. Liu, X. Gong, X. Wang, H. Li. Conditional Adversarial Generative Flow for Controllable
Image Synthesis. CVPR 2019.
12. D. J. Rezende and S. Mohamed. Variational Inference with Normalizing Flows. ICML 2015.