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stat.ME2026
Tucker Diffusion Model for High-dimensional Tensor Generation
Jianhua Guo, Xinbing Kong, Zeyu Li +1
Statistical inference on large-dimensional tensor data has been extensively studied in the literature and widely used in economics, biology, machine learning, and other fields, but…
cs.LG2026
Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes
Hongkun Dou, Zike Chen, Zeyu Li +3
Diffusion models have gained prominence as powerful generative tools for solving inverse problems due to their ability to model complex data distributions. However, existing method…
cs.LG2026
Variational Trajectory Optimization of Anisotropic Diffusion Schedules
Pengxi Liu, Zeyu Michael Li, Xiang Cheng
We introduce a variational framework for diffusion models with anisotropic noise schedules parameterized by a matrix-valued path that allocates noise across subspaces. Cen…