1 citations · 3 across the 15 of their papers we have counts for
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Pro-t-VAE: Closed-Form Student's t Mixtures for Robust Prototype Discovery
Zhikang Xu, Jiarui Xing, Jian Wang
We present a robust deep generative framework for unsupervised image prototype discovery, built on a heavy-tailed Student's t mixture prior, that bridges statistical robustness and…
Geodesic-informed Generative Diffusion Model For Topology-preserved Image Video Generation
Nian Wu, Nivetha Jayakumar, Jiarui Xing +1
Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, including but not limited to synthesis, reconstruction, and segmentatio…
Deep Image Prototype Learning with Geometric Heat-Kernel Priors
Jiarui Xing, Tal Zeevi, Nian Wu +1
Learning unsupervised representations of medical imaging cohorts can reveal anatomically meaningful prototypes without expert labels, which are often noisy and fail to capture true…
Uncertainty in a Single Pass: A Closed-Form Identity for One-Step Flow Matching
Jiarui Xing, Song Wang, Jian Wang
Flow matching provides a highly effective framework for generative modeling, yet estimating the uncertainty of its generated samples remains a fundamental challenge. Existing metho…
PathoSyn: Imaging-Pathology MRI Synthesis via Disentangled Deviation Diffusion
Jian Wang, Sixing Rong, Jiarui Xing +2
We present PathoSyn, a unified generative framework for Magnetic Resonance Imaging (MRI) image synthesis that reformulates imaging-pathology as a disentangled additive deviation on…