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- talk-glouppe-cse21.pdf
- Masashi Sugiyama, Density Ratio Estimation in Machine Learning Slides
- Machine Learning Trick of the Day (7): Density Ratio Trick— Shakir Mohammed
References
Delaunoy, Arnaud, Joeri Hermans, François Rozet, Antoine Wehenkel, and Gilles Louppe. 2022. “Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation.” arXiv.
Fukumizu, Kenji. 2003. “Likelihood Ratio of Unidentifiable Models and Multilayer Neural Networks.” The Annals of Statistics 31 (3): 833–51.
Handcock, Mark S., and Martina Morris. 1998. “Relative Distribution Methods.” Sociological Methodology 28 (1): 53–97.
Menon, Aditya, and Cheng Soon Ong. 2016. “Linking Losses for Density Ratio and Class-Probability Estimation.” In Proceedings of The 33rd International Conference on Machine Learning, 304–13. PMLR.
Miller, Benjamin Kurt, Christoph Weniger, and Patrick Forré. 2022. “Contrastive Neural Ratio Estimation.” In.
Rozet, François, and Gilles Louppe. 2021. “Arbitrary Marginal Neural Ratio Estimation for Simulation-Based Inference.” arXiv.
Sugiyama, Masashi, Taiji Suzuki, and Takafumi Kanamori. 2012. Density Ratio Estimation in Machine Learning. Cambridge: Cambridge University Press.
———. n.d. “Density Ratio Estimation: A Comprehensive Review,” 22.
Sugiyama, Masashi, Ichiro Takeuchi, Taiji Suzuki, Takafumi Kanamori, Hirotaka Hachiya, and Daisuke Okanohara. 2010. “Conditional Density Estimation via Least-Squares Density Ratio Estimation.” In International Conference on Artificial Intelligence and Statistics, 781–88.
Thomas, Owen, Ritabrata Dutta, Jukka Corander, Samuel Kaski, and Michael U. Gutmann. 2020. “Likelihood-Free Inference by Ratio Estimation.” arXiv.
Tiao, Louis C, Aaron Klein, Cédric Archambeau, Edwin V Bonilla, Matthias Seeger, and Fabio Ramos. 2020. “Bayesian Optimization by Density Ratio Estimation.” In, 8.
Usman, Ben, Avneesh Sud, Nick Dufour, and Kate Saenko. 2020. “Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment.” In Advances in Neural Information Processing Systems, 33:21118–29. Curran Associates, Inc.
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