DiSI disentangles stochastic interpolants into separate generation and regression paths, allowing controllable transitions between regression and generative image restoration with a unified few-step sampler.
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Advances in neural information processing systems34, 8780–8794 (2021)
12 Pith papers cite this work. Polarity classification is still indexing.
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GeoEdit constructs local tangent frames from small perturbations to initial noise, enabling Jacobian-free on-manifold edits in diffusion models via alternating tangent steps and diffusion projections.
Pretrained autoencoders in medical latent diffusion encode discriminative features well for reconstruction but structure their latent spaces in ways that hinder classifier learning, a gap that persists across architectures and is not closed by domain fine-tuning.
A hybrid-conditioned diffusion transformer generates 2D topologies matching SIMP solutions within 1% compliance error using only five denoising steps.
Geometry-preserving losses based on tangent-space distances improve blackbox GAN adaptation to shifted distributions compared with standard losses.
VS-DDPM accelerates 3D diffusion models for medical modality translation, reaching SOTA Dice scores of 0.80-0.88 and SSIM 0.95 on missing MRI synthesis in BraTS2025 while remaining competitive on tumor removal and sCT tasks.
TabSCM produces causally consistent tabular data by orienting a CPDAG into a DAG, fitting root marginals with KDE, and using conditional diffusion plus trees for child nodes, outperforming GANs and diffusion baselines on fidelity, utility, and privacy across seven datasets.
DiffHDR converts LDR videos to HDR by formulating the task as generative radiance inpainting in a video diffusion model's latent space, using Log-Gamma encoding and synthesized training data to achieve better fidelity and stability than prior methods.
DE-CM reaches state-of-the-art one-step FID of 1.70 on ImageNet 256x256 by decomposing PF-ODE trajectories into three critical sub-trajectories and using flow matching plus N2N mapping for stability.
SEGS constructs structural energy in the PCA subspace of U-Net features and injects its gradient into the denoising process to improve multi-view consistency in text-to-3D generation.
SHIFT learns and applies steering vectors to selected layers and timesteps in DiT models to suppress concepts, shift styles, or bias objects while keeping image quality and prompt adherence intact.
citing papers explorer
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Disentangling Generation and Regression in Stochastic Interpolants for Controllable Image Restoration
DiSI disentangles stochastic interpolants into separate generation and regression paths, allowing controllable transitions between regression and generative image restoration with a unified few-step sampler.
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GeoEdit: Local Frames for Fast, Training-Free On-Manifold Editing in Diffusion Models
GeoEdit constructs local tangent frames from small perturbations to initial noise, enabling Jacobian-free on-manifold edits in diffusion models via alternating tangent steps and diffusion projections.
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The Learnability Gap in Medical Latent Diffusion
Pretrained autoencoders in medical latent diffusion encode discriminative features well for reconstruction but structure their latent spaces in ways that hinder classifier learning, a gap that persists across architectures and is not closed by domain fine-tuning.
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Diffusion Transformers with Hybrid Conditioning for Structural Optimization
A hybrid-conditioned diffusion transformer generates 2D topologies matching SIMP solutions within 1% compliance error using only five denoising steps.
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Geometry Preserving Loss Functions Promote Improved Adaptation of Blackbox Generative Model
Geometry-preserving losses based on tangent-space distances improve blackbox GAN adaptation to shifted distributions compared with standard losses.
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VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation
VS-DDPM accelerates 3D diffusion models for medical modality translation, reaching SOTA Dice scores of 0.80-0.88 and SSIM 0.95 on missing MRI synthesis in BraTS2025 while remaining competitive on tumor removal and sCT tasks.
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TabSCM: A practical Framework for Generating Realistic Tabular Data
TabSCM produces causally consistent tabular data by orienting a CPDAG into a DAG, fitting root marginals with KDE, and using conditional diffusion plus trees for child nodes, outperforming GANs and diffusion baselines on fidelity, utility, and privacy across seven datasets.
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DiffHDR: Re-Exposing LDR Videos with Video Diffusion Models
DiffHDR converts LDR videos to HDR by formulating the task as generative radiance inpainting in a video diffusion model's latent space, using Log-Gamma encoding and synthesized training data to achieve better fidelity and stability than prior methods.
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Dual-End Consistency Model
DE-CM reaches state-of-the-art one-step FID of 1.70 on ImageNet 256x256 by decomposing PF-ODE trajectories into three critical sub-trajectories and using flow matching plus N2N mapping for stability.
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Structural Energy Guidance for View-Consistent Text-to-3D Generation
SEGS constructs structural energy in the PCA subspace of U-Net features and injects its gradient into the denoising process to improve multi-view consistency in text-to-3D generation.
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SHIFT: Steering Hidden Intermediates in Flow Transformers
SHIFT learns and applies steering vectors to selected layers and timesteps in DiT models to suppress concepts, shift styles, or bias objects while keeping image quality and prompt adherence intact.
- Generative structure search for efficient and diverse discovery of molecular and crystal structures