Poster "denoising diffusion probabilistic models" Papers

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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

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