1 code implementation • 31 Oct 2023 • Mingxuan Yi, Song Liu
Variational inference is a technique that approximates a target distribution by optimizing within the parameter space of variational families.
1 code implementation • 24 May 2023 • Song Liu, Jiahao Yu, Jack Simons, Mingxuan Yi, Mark Beaumont
To perform such movements we need to calculate the corresponding velocity fields which include a density ratio function between these two distributions.
no code implementations • 2 Feb 2023 • Mingxuan Yi, Zhanxing Zhu, Song Liu
The conventional understanding of adversarial training in generative adversarial networks (GANs) is that the discriminator is trained to estimate a divergence, and the generator learns to minimize this divergence.
no code implementations • pproximateinference AABI Symposium 2022 • Mingxuan Yi, Song Liu
For example, it is not a proper metric, i. e., it is non-symmetric and does not preserve the triangle inequality.
no code implementations • 15 Feb 2020 • Song Liu, Yulong Zhang, Mingxuan Yi, Mladen Kolar
Density Ratio Estimation has attracted attention from the machine learning community due to its ability to compare the underlying distributions of two datasets.