RF-Sampling enhances flow matching models by implicitly performing gradient ascent on text-image alignment scores via linear textual combinations and flow inversion.
Diffusion models: A comprehensive survey of methods and applications,
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UNVERDICTED 4representative citing papers
A language-driven system generates semantically consistent multimodal textures from text prompts by linking autoregressive haptic models and diffusion-based visuals through a shared latent representation.
Hybrid quantum-classical corrective diffusion model improves MAE and CRPS on 2020 validation wind data but exhibits a generalization gap on 2021 out-of-distribution tests.
An I²SB diffusion model for CT FOV extension delivers RMSE of 49.8 HU on simulated data and 152.0 HU on real data with 0.19 s per-slice inference, over 700 times faster than cDDPM.
citing papers explorer
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Reflective Flow Sampling Enhancement
RF-Sampling enhances flow matching models by implicitly performing gradient ascent on text-image alignment scores via linear textual combinations and flow inversion.
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Language-Guided Multimodal Texture Authoring via Generative Models
A language-driven system generates semantically consistent multimodal textures from text prompts by linking autoregressive haptic models and diffusion-based visuals through a shared latent representation.
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Hybrid Quantum-Classical Corrective Diffusion Modeling for Meteorological Downscaling
Hybrid quantum-classical corrective diffusion model improves MAE and CRPS on 2020 validation wind data but exhibits a generalization gap on 2021 out-of-distribution tests.
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Efficient Image-to-Image Schr\"odinger Bridge for CT Field of View Extension
An I²SB diffusion model for CT FOV extension delivers RMSE of 49.8 HU on simulated data and 152.0 HU on real data with 0.19 s per-slice inference, over 700 times faster than cDDPM.