Improved diffusion generative models with subspaces

This is a repository for paper Mechanistic Dissection of Cross-Attention Subspaces in Text-to-Image Diffusion Models @AAAI'26

Official PyTorch implementation of "Shallow Diffuse: Robust and Invisible Watermarking through Low-Dimensional Subspaces in Diffusion Models"

[CVPR 2025] Self-Learning Hyperspectral and Multispectral Image Fusion via Adaptive Residual Guided Subspace Diffusion Model

[ICLR 2025] codes of PSR-SCI: Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement

[CVPR 2025] Self-Learning Hyperspectral and Multispectral Image Fusion via Adaptive Residual Guided Subspace Diffusion Model

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A deep nonlinear subspace modeling and reconstruction for diffusion-weighted imaging using denoising auto-encoder

Code for the paper - Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted

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Code for Diffusion Process with Structural Change for Subspace Clustering

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The code of 'Diffusion subspace clustering for hyperspectral images'.

code of paper "Adaptive Subspace Clustering via Diffusion Probabilistic Autoencoders"

The Krylov subspace implemented ParaExp algorithm for a large-scale linear switched system constructed from the 2D convection-diffusion equation

In this work, the 2-D Diffusion equation is solved on a structured grid using the Finite Difference Method, This is done using a parallelized code, utilizing the PETSc library’s C interface. Krylov Subspace Solvers were utilized.