4 papers
Variational Masked Diffusion Models
Yichi Zhang, Alex Schwing, Zhizhen Zhao
Masked diffusion models have recently emerged as a flexible framework for discrete generative modeling. However, a key limitation of standard masked diffusion is its inability to e…
Hierarchical Rectified Flow Matching with Mini-Batch Couplings
Yichi Zhang, Yici Yan, Alex Schwing +1
Flow matching has emerged as a compelling generative modeling approach that is widely used across domains. To generate data via a flow matching model, an ordinary differential equa…
Towards Hierarchical Rectified Flow
Yichi Zhang, Yici Yan, Alex Schwing +1
We formulate a hierarchical rectified flow to model data distributions. It hierarchically couples multiple ordinary differential equations (ODEs) and defines a time-differentiable…
Boosting Test Performance with Importance Sampling--a Subpopulation Perspective
Hongyu Shen, Zhizhen Zhao
Despite empirical risk minimization (ERM) is widely applied in the machine learning community, its performance is limited on data with spurious correlation or subpopulation that is…