"denoising diffusion probabilistic models" Papers
12 papers found
Conference
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion Models
Wentao Qu, Jing Wang, Yongshun Gong et al.
CVPR 2025arXiv:2411.16308
9
citations
Deep MMD Gradient Flow without adversarial training
Alexandre Galashov, Valentin De Bortoli, Arthur Gretton
ICLR 2025arXiv:2405.06780
10
citations
Denoising Levy Probabilistic Models
Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus
ICLR 2025
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration
Mingyang Song, Xiaoye Qu, Jiawei Zhou et al.
CVPR 2025arXiv:2503.12821
3
citations
Graph Diffusion that can Insert and Delete
Matteo Ninniri, Marco Podda, Davide Bacciu
NEURIPS 2025arXiv:2506.15725
1
citations
Improved Sampling Of Diffusion Models In Fluid Dynamics With Tweedie's Formula
Youssef Shehata, Benjamin Holzschuh, Nils Thuerey
ICLR 2025oral
3
citations
OCTDiff: Bridged Diffusion Model for Portable OCT Super-Resolution and Enhancement
Ye Tian, Angela McCarthy, Gabriel Gomide et al.
NEURIPS 2025spotlight
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang et al.
ICLR 2025oralarXiv:2410.05805
7
citations
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale
Candi Zheng, Yuan LAN
ICML 2024arXiv:2312.07586
16
citations
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos et al.
ICML 2024arXiv:2405.19201
4
citations
Temporal Residual Guided Diffusion Framework for Event-Driven Video Reconstruction
Lin Zhu, Yunlong Zheng, Yijun Zhang et al.
ECCV 2024arXiv:2407.10636
6
citations
Unified Framework for Diffusion Generative Models in SO(3): Applications in Computer Vision and Astrophysics
Yesukhei Jagvaral, Francois Lanusse, Rachel Mandelbaum
AAAI 2024paperarXiv:2312.11707
9
citations