2 citations · 2 across the 4 of their papers we have counts for
5 papers
Zero-Flow Two-Sample Tests
Yakun Wang, Leyang Wang, Song Liu +1
Motivated by the success of modern flow-based generative models in modeling complex data, we study two-sample testing through the lens of flow-based methods. We propose the Zero-Fl…
Zero-Flow Encoders
Yakun Wang, Leyang Wang, Song Liu +1
Flow-based methods have achieved significant success in various generative modeling tasks, capturing nuanced details within complex data distributions. However, few existing works…
Direct Fisher Score Estimation for Likelihood Maximization
Sherman Khoo, Yakun Wang, Song Liu +1
We study the problem of likelihood maximization when the likelihood function is intractable but model simulations are readily available. We propose a sequential, gradient-based opt…
Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold
Song Liu, Leyang Wang, Yakun Wang
Optimising probabilistic models is a well-studied field in statistics. However, its connection with the training of generative models remains largely under-explored. In this paper,…
Machine Learning Based Probe Skew Correction for High-frequency BH Loop Measurements
Yakun Wang, Song Liu, Jun Wang +2
Experimental characterization of magnetic components has grown to be increasingly important to understand and model their behaviours in high-frequency PWM converters. The BH loop m…