Prof. Jong Chul Ye from KAIST, Korea: Diffusion Models for Computational Imaging Problems

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Computational Imaging SPACE Webinar Series: Jong Chul Ye, KAIST Computational Imaging SPACE Webinar Series: Jong Chul Ye, KAIST
Webinar #13: Accelerating Conditional Diffusion Models for Inverse Problems - Prof. Jung Chul Ye Webinar #13: Accelerating Conditional Diffusion Models for Inverse Problems - Prof. Jung Chul Ye
Beyond the Patterns - Episode 7 - Jong Chul Ye - GAN for Medical image Reconstruction Beyond the Patterns - Episode 7 - Jong Chul Ye - GAN for Medical image Reconstruction
GenAI Diffusion Models mini-symposium: “Diffusion Models for Inverse Problems in Medical Imaging” GenAI Diffusion Models mini-symposium: “Diffusion Models for Inverse Problems in Medical Imaging”
MedAI #92: Generative Diffusion Models for Medical Imaging | Hyungjin Chung MedAI #92: Generative Diffusion Models for Medical Imaging | Hyungjin Chung
Video from ISMRM 2019: Jong Chul Ye on machine learning and data reconstruction Video from ISMRM 2019: Jong Chul Ye on machine learning and data reconstruction
QLIP: Text Embedding Knows How to Quantize Text-Guided Diffusion Models (ICCV2025) QLIP: Text Embedding Knows How to Quantize Text-Guided Diffusion Models (ICCV2025)
[ICCV 2025] GeoMan: Temporally Consistent Human Geometry Estimation using Image-to-Video Diffusion [ICCV 2025] GeoMan: Temporally Consistent Human Geometry Estimation using Image-to-Video Diffusion