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…
Efficient Implicit Neural Compression of Point Clouds via Learnable Activation in Latent Space
Yichi Zhang, Qianqian Yang
Implicit Neural Representations (INRs), also known as neural fields, have emerged as a powerful paradigm in deep learning, parameterizing continuous spatial fields using coordinate…
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…