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We formalize an equivalence between two popular methods for Bayesian inference: Stein variational gradient descent (SVGD) and black-box variational inference (BBVI).
The geometry of dissipative evolution equations: the porous medium equation
Otto, F · 2001
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Sticking the landing: Simple, lower-variance gradient estimators for variational inference
Roeder, G., Wu, Y., and Duvenaud, D. K · 2004
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Gradient flows: in metric spaces and in the space of probability measures
Ambrosio, L., Gigli, N., and Savaré, G · 2008
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Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Auto-encoding variational Bayes
Kingma, D. P. and Welling, M · 2014
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Black box variational inference
Ranganath, R., Gerrish, S., and Blei, D · 2014
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Stein variational gradient descent: A general purpose Bayesian inference algorithm
Liu, Q. and Wang, D · 2016
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Learning to draw samples with amortized Stein variational gradient descent
Feng, Y., Wang, D., and Liu, Q · 2017
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Stein variational gradient descent as gradient flow
Liu, Q · 2017
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Neural tangent kernel: Convergence and generalization in neural networks
Jacot, A., Gabriel, F., and Hongler, C · 2018
Cited alongside, same era.
Probability functional descent: A unifying perspective on GANs, variational inference, and reinforcement learning
Chu, C., Blanchet, J., and Glynn, P · 2019
Later among the works it cites.
On the geometry of Stein variational gradient descent
Duncan, A., Nüsken, N., and Szpruch, L · 2019
Later among the works it cites.
Understanding and accelerating particle-based variational inference
Liu, C., Zhuo, J., Cheng, P., Zhang, R., and Zhu, J · 2019
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Scaling limit of the Stein variational gradient descent: The mean field regime
Lu, J., Lu, Y., and Nolen, J · 2019
Later among the works it cites.
Smoothness and stability in GANs
Chu, C., Minami, K., and Fukumizu, K · 2020
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