1. Spiking Denoising Diffusion Probabilistic Models
    Jiahang Cao, Ziqing Wang, Hanzhong Guo, Hao Cheng, Qiang Zhang, Renjing Xu
    arXiv 2023. Paper  
    2023-06-29
    2023-06-29
  2. DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data
    Jingyuan Zhu, Huimin Ma, Jiansheng Chen, Jian Yuan
    arXiv 2023. Paper  
    2023-06-25
    2023-06-25
  3. Decoupled Diffusion Models with Explicit Transition Probability
    Yuhang Huang, Zheng Qin, Xinwang Liu, Kai Xu
    arXiv 2023. Paper  
    2023-06-23
    2023-06-23
  4. Continuous Layout Editing of Single Images with Diffusion Models
    Zhiyuan Zhang, Zhitong Huang, Jing Liao
    arXiv 2023. Paper  
    2023-06-22
    2023-06-22
  5. Semi-Implicit Denoising Diffusion Models (SIDDMs)
    Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, kayhan Batmanghelich, Tingbo Hou
    arXiv 2023. Paper  
    2023-06-21
    2023-06-21
  6. Eliminating Lipschitz Singularities in Diffusion Models
    Zhantao Yang, Ruili Feng, Han Zhang, Yujun Shen, Kai Zhu, Lianghua Huang, Yifei Zhang, Yu Liu, Deli Zhao, Jingren Zhou, Fan Cheng
    arXiv 2023. Paper  
    2023-06-20
    2023-06-20
  7. GD-VDM: Generated Depth for better Diffusion-based Video Generation
    Ariel Lapid, Idan Achituve, Lior Bracha, Ethan Fetaya
    arXiv 2023. Paper  
    2023-06-19
    2023-06-19
  8. Image Harmonization with Diffusion Model
    Jiajie Li, Jian Wang, Chen Wang, Jinjun Xiong
    arXiv 2023. Paper  
    2023-06-17
    2023-06-17
  9. OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
    Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  10. Relation-Aware Diffusion Model for Controllable Poster Layout Generation
    Fengheng Li, An Liu, Wei Feng, Honghe Zhu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  11. Fast Training of Diffusion Models with Masked Transformers
    Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar
    arXiv 2023. Paper   Github  
    2023-06-15
    2023-06-15
  12. Conditional Human Sketch Synthesis with Explicit Abstraction Control
    Dar-Yen Chen
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  13. Training Diffusion Classifiers with Denoising Assistance
    Chandramouli Sastry, Sri Harsha Dumpala, Sageev Oore
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  14. DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$
    Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf
    arXiv 2023. Paper  
    2023-06-13
    2023-06-13
  15. Fast Diffusion Model
    Zike Wu, Pan Zhou, Kenji Kawaguchi, Hanwang Zhang
    arXiv 2023. Paper   Github  
    2023-06-12
    2023-06-12
  16. Interpreting and Improving Diffusion Models Using the Euclidean Distance Function
    Frank Permenter, Chenyang Yuan
    arXiv 2023. Paper  
    2023-06-08
    2023-06-08
  17. Multi-Architecture Multi-Expert Diffusion Models
    Yunsung Lee, Jin-Young Kim, Hyojun Go, Myeongho Jeong, Shinhyeok Oh, Seungtaek Choi
    arXiv 2023. Paper  
    2023-06-08
    2023-06-08
  18. ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process
    Changyao Tian, Chenxin Tao, Jifeng Dai, Hao Li, Ziheng Li, Lewei Lu, Xiaogang Wang, Hongsheng Li, Gao Huang, Xizhou Zhu
    arXiv 2023. Paper  
    2023-06-08
    2023-06-08
  19. Faster Training of Diffusion Models and Improved Density Estimation via Parallel Score Matching
    Etrit Haxholli, Marco Lorenzi
    arXiv 2023. Paper  
    2023-06-05
    2023-06-05
  20. Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models
    Andrew F. Luo, Margaret M. Henderson, Leila Wehbe, Michael J. Tarr
    arXiv 2023. Paper  
    2023-06-05
    2023-06-05
  21. Video Diffusion Models with Local-Global Context Guidance
    Siyuan Yang, Lu Zhang, Yu Liu, Zhizhuo Jiang, You He
    IJCAI 2023. Paper   Github  
    2023-06-05
    2023-06-05
  22. Temporal Dynamic Quantization for Diffusion Models
    Junhyuk So, Jungwon Lee, Daehyun Ahn, Hyungjun Kim, Eunhyeok Park
    arXiv 2023. Paper  
    2023-06-04
    2023-06-04
  23. Conditional Generation from Unconditional Diffusion Models using Denoiser Representations
    Alexandros Graikos, Srikar Yellapragada, Dimitris Samaras
    arXiv 2023. Paper  
    2023-06-02
    2023-06-02
  24. Addressing Negative Transfer in Diffusion Models
    Hyojun Go, JinYoung Kim, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh, Hyeongdon Moon, Seungtaek Choi
    arXiv 2023. Paper  
    2023-06-01
    2023-06-01
  25. Addressing Discrepancies in Semantic and Visual Alignment in Neural Networks
    Natalie Abreu, Nathan Vaska, Victoria Helus
    arXiv 2023. Paper  
    2023-06-01
    2023-06-01
  26. Differential Diffusion: Giving Each Pixel Its Strength
    Eran Levin, Ohad Fried
    arXiv 2023. Paper  
    2023-06-01
    2023-06-01
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    Nico Giambi, Giuseppe Lisanti
    arXiv 2023. Paper  
    2023-06-01
    2023-06-01
  28. Spontaneous symmetry breaking in generative diffusion models
    Gabriel Raya, Luca Ambrogioni
    arXiv 2023. Paper  
    2023-05-31
    2023-05-31
  29. A Geometric Perspective on Diffusion Models
    Defang Chen, Zhenyu Zhou, Jian-Ping Mei, Chunhua Shen, Chun Chen, Can Wang
    arXiv 2023. Paper  
    2023-05-31
    2023-05-31
  30. Towards Accurate Data-free Quantization for Diffusion Models
    Changyuan Wang, Ziwei Wang, Xiuwei Xu, Yansong Tang, Jie Zhou, Jiwen Lu
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  31. Ambient Diffusion: Learning Clean Distributions from Corrupted Data
    Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alexandros G. Dimakis, Adam Klivans
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  32. One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models
    Ba-Hien Tran, Giulio Franzese, Pietro Michiardi, Maurizio Filippone
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  33. Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification
    Yifei Liu, Rex Shen, Xiaotong Shen
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  34. Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors
    Paul S. Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Ethan Cohen, Aidan J. Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, Kenneth A. Norman, Tanishq Mathew Abraham
    arXiv 2023. Paper   Github  
    2023-05-29
    2023-05-29
  35. Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
    Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang
    arXiv 2023. Paper  
    2023-05-29
    2023-05-29
  36. BRIGHT: Bi-level Feature Representation of Image Collections using Groups of Hash Tables
    Dingdong Yang, Yizhi Wang, Ali Mahdavi-Amiri, Hao Zhang
    arXiv 2023. Paper   Project  
    2023-05-29
    2023-05-29
  37. Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling
    Tianqi Chen, Mingyuan Zhou
    ICML 2023. Paper   Github  
    2023-05-28
    2023-05-28
  38. Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
    Jingyuan Sun, Mingxiao Li, Zijiao Chen, Yunhao Zhang, Shaonan Wang, Marie-Francine Moens
    arXiv 2023. Paper  
    2023-05-26
    2023-05-26
  39. Unifying GANs and Score-Based Diffusion as Generative Particle Models
    Jean-Yves Franceschi, Mike Gartrell, Ludovic Dos Santos, Thibaut Issenhuth, Emmanuel de Bézenac, Mickaël Chen, Alain Rakotomamonjy
    arXiv 2023. Paper  
    2023-05-25
    2023-05-25
  40. UDPM: Upsampling Diffusion Probabilistic Models
    Shady Abu-Hussein, Raja Giryes
    arXiv 2023. Paper  
    2023-05-25
    2023-05-25
  41. Trans-Dimensional Generative Modeling via Jump Diffusion Models
    Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet
    arXiv 2023. Paper  
    2023-05-25
    2023-05-25
  42. Parallel Sampling of Diffusion Models
    Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari
    arXiv 2023. Paper   Github  
    2023-05-25
    2023-05-25
  43. On the Generalization of Diffusion Model
    Mingyang Yi, Jiacheng Sun, Zhenguo Li
    arXiv 2023. Paper  
    2023-05-24
    2023-05-24
  44. Robust Classification via a Single Diffusion Model
    Huanran Chen, Yinpeng Dong, Zhengyi Wang, Xiao Yang, Chengqi Duan, Hang Su, Jun Zhu
    arXiv 2023. Paper  
    2023-05-24
    2023-05-24
  45. Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
    Mingxiao Li, Tingyu Qu, Wei Sun, Marie-Francine Moens
    arXiv 2023. Paper  
    2023-05-24
    2023-05-24
  46. DuDGAN: Improving Class-Conditional GANs via Dual-Diffusion
    Taesun Yeom, Minhyeok Lee
    arXiv 2023. Paper  
    2023-05-24
    2023-05-24
  47. VDT: An Empirical Study on Video Diffusion with Transformers
    Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo, Zhiwu Lu, Ping Luo, Mingyu Ding
    arXiv 2023. Paper   Github  
    2023-05-22
    2023-05-22
  48. Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity
    Zijiao Chen, Jiaxin Qing, Juan Helen Zhou
    arXiv 2023. Paper   Project  
    2023-05-19
    2023-05-19
  49. Catch-Up Distillation: You Only Need to Train Once for Accelerating Sampling
    Shitong Shao, Xu Dai, Shouyi Yin, Lujun Li, Huanran Chen, Yang Hu
    arXiv 2023. Paper  
    2023-05-18
    2023-05-18
  50. Structural Pruning for Diffusion Models
    Gongfan Fang, Xinyin Ma, Xinchao Wang
    arXiv 2023. Paper   Github  
    2023-05-18
    2023-05-18
  51. Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces
    Javier E Santos, Zachary R. Fox, Nicholas Lubbers, Yen Ting Lin
    arXiv 2023. Paper  
    2023-05-18
    2023-05-18
  52. PTQD: Accurate Post-Training Quantization for Diffusion Models
    Yefei He, Luping Liu, Jing Liu, Weijia Wu, Hong Zhou, Bohan Zhuang
    arXiv 2023. Paper  
    2023-05-18
    2023-05-18
  53. Controllable Mind Visual Diffusion Model
    Bohan Zeng, Shanglin Li, Xuhui Liu, Sicheng Gao, Xiaolong Jiang, Xu Tang, Yao Hu, Jianzhuang Liu, Baochang Zhang
    arXiv 2023. Paper  
    2023-05-17
    2023-05-17
  54. Analyzing Bias in Diffusion-based Face Generation Models
    Malsha V. Perera, Vishal M. Patel
    arXiv 2023. Paper  
    2023-05-10
    2023-05-10
  55. LEO: Generative Latent Image Animator for Human Video Synthesis
    Yaohui Wang, Xin Ma, Xinyuan Chen, Antitza Dantcheva, Bo Dai, Yu Qiao
    arXiv 2023. Paper   Project   Github  
    2023-05-06
    2023-05-06
  56. Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
    Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu
    ICML 2023. Paper  
    2023-05-06
    2023-05-06
  57. Iterative α-(de)Blending: a Minimalist Deterministic Diffusion Model
    Eric Heitz, Laurent Belcour, Thomas Chambon
    SIGGRAPH 2023. Paper  
    2023-05-05
    2023-05-05
  58. Reconstructing seen images from human brain activity via guided stochastic search
    Reese Kneeland, Jordyn Ojeda, Ghislain St-Yves, Thomas Naselaris
    arXiv 2023. Paper  
    2023-04-30
    2023-04-30
  59. Motion-Conditioned Diffusion Model for Controllable Video Synthesis
    Tsai-Shien Chen, Chieh Hubert Lin, Hung-Yu Tseng, Tsung-Yi Lin, Ming-Hsuan Yang
    arXiv 2023. Paper   Project  
    2023-04-27
    2023-04-27
  60. Score-based Generative Modeling Through Backward Stochastic Differential Equations: Inversion and Generation
    Zihao Wang
    arXiv 2023. Paper  
    2023-04-26
    2023-04-26
  61. Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
    Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou
    arXiv 2023. Paper  
    2023-04-25
    2023-04-25
  62. Exploring Compositional Visual Generation with Latent Classifier Guidance
    Changhao Shi, Haomiao Ni, Kai Li, Shaobo Han, Mingfu Liang, Martin Renqiang Min
    CVPR Workshop 2023. Paper  
    2023-04-25
    2023-04-25
  63. Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior
    Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb
    arXiv 2023. Paper  
    2023-04-24
    2023-04-24
  64. LaMD: Latent Motion Diffusion for Video Generation
    Yaosi Hu, Zhenzhong Chen, Chong Luo
    arXiv 2023. Paper  
    2023-04-23
    2023-04-23
  65. Lookahead Diffusion Probabilistic Models for Refining Mean Estimation
    Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
    CVPR 2023. Paper   Github  
    2023-04-22
    2023-04-22
  66. NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models
    Seung Wook Kim, Bradley Brown, Kangxue Yin, Karsten Kreis, Katja Schwarz, Daiqing Li, Robin Rombach, Antonio Torralba, Sanja Fidler
    CVPR 2023. Paper  
    2023-04-19
    2023-04-19
  67. Attributing Image Generative Models using Latent Fingerprints
    Guangyu Nie, Changhoon Kim, Yezhou Yang, Yi Ren
    arXiv 2023. Paper  
    2023-04-17
    2023-04-17
  68. DCFace: Synthetic Face Generation with Dual Condition Diffusion Model
    Minchul Kim, Feng Liu, Anil Jain, Xiaoming Liu
    arXiv 2023. Paper   Github  
    2023-04-14
    2023-04-14
  69. Memory Efficient Diffusion Probabilistic Models via Patch-based Generation
    Shinei Arakawa, Hideki Tsunashima, Daichi Horita, Keitaro Tanaka, Shigeo Morishima
    arXiv 2023. Paper  
    2023-04-14
    2023-04-14
  70. Identity Encoder for Personalized Diffusion
    Yu-Chuan Su, Kelvin C.K. Chan, Yandong Li, Yang Zhao, Han Zhang, Boqing Gong, Huisheng Wang, Xuhui Jia
    arXiv 2023. Paper  
    2023-04-14
    2023-04-14
  71. DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning
    Enze Xie, Lewei Yao, Han Shi, Zhili Liu, Daquan Zhou, Zhaoqiang Liu, Jiawei Li, Zhenguo Li
    arXiv 2023. Paper  
    2023-04-13
    2023-04-13
  72. RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment
    Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang
    arXiv 2023. Paper  
    2023-04-13
    2023-04-13
  73. DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion
    Johanna Karras, Aleksander Holynski, Ting-Chun Wang, Ira Kemelmacher-Shlizerman
    arXiv 2023. Paper   Project   Github  
    2023-04-12
    2023-04-12
  74. Binary Latent Diffusion
    Ze Wang, Jiang Wang, Zicheng Liu, Qiang Qiu
    arXiv 2023. Paper  
    2023-04-10
    2023-04-10
  75. Reflected Diffusion Models
    Aaron Lou, Stefano Ermon
    ICML 2023. Paper   Project   Github  
    2023-04-10
    2023-04-10
  76. Diffusion Models as Masked Autoencoders
    Chen Wei, Karttikeya Mangalam, Po-Yao Huang, Yanghao Li, Haoqi Fan, Hu Xu, Huiyu Wang, Cihang Xie, Alan Yuille, Christoph Feichtenhofer
    arXiv 2023. Paper   Project  
    2023-04-06
    2023-04-06
  77. Few-shot Semantic Image Synthesis with Class Affinity Transfer
    Marlène Careil, Jakob Verbeek, Stéphane Lathuilière
    CVPR 2023. Paper  
    2023-04-05
    2023-04-05
  78. EGC: Image Generation and Classification via a Diffusion Energy-Based Model
    Qiushan Guo, Chuofan Ma, Yi Jiang, Zehuan Yuan, Yizhou Yu, Ping Luo
    arxiv 2023. Paper   Project  
    2023-04-04
    2023-04-04
  79. 3D-aware Image Generation using 2D Diffusion Models
    Jianfeng Xiang, Jiaolong Yang, Binbin Huang, Xin Tong
    arXiv 2023. Paper   Project  
    2023-03-31
    2023-03-31
  80. -Diff: Infinite Resolution Diffusion with Subsampled Mollified States
    Sam Bond-Taylor, Chris G. Willcocks
    arXiv 2023. Paper  
    2023-03-31
    2023-03-31
  81. A Closer Look at Parameter-Efficient Tuning in Diffusion Models
    Chendong Xiang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
    arXiv 2023. Paper  
    2023-03-31
    2023-03-31
  82. DiffCollage: Parallel Generation of Large Content with Diffusion Models
    Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu
    CVPR 2023. Paper   Project  
    2023-03-30
    2023-03-30
  83. Consistent View Synthesis with Pose-Guided Diffusion Models
    Hung-Yu Tseng, Qinbo Li, Changil Kim, Suhib Alsisan, Jia-Bin Huang, Johannes Kopf
    CVPR 2023. Paper  
    2023-03-30
    2023-03-30
  84. Token Merging for Fast Stable Diffusion
    Daniel Bolya, Judy Hoffman
    arXiv 2023. Paper   Github  
    2023-03-30
    2023-03-30
  85. Masked Diffusion Transformer is a Strong Image Synthesizer
    Shanghua Gao, Pan Zhou, Ming-Ming Cheng, Shuicheng Yan
    arXiv 2023. Paper   Github  
    2023-03-25
    2023-03-25
  86. Conditional Image-to-Video Generation with Latent Flow Diffusion Models
    Haomiao Ni, Changhao Shi, Kai Li, Sharon X. Huang, Martin Renqiang Min
    CVPR 2023. Paper   Github  
    2023-03-24
    2023-03-24
  87. NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation
    Shengming Yin, Chenfei Wu, Huan Yang, Jianfeng Wang, Xiaodong Wang, Minheng Ni, Zhengyuan Yang, Linjie Li, Shuguang Liu, Fan Yang, Jianlong Fu, Gong Ming, Lijuan Wang, Zicheng Liu, Houqiang Li, Nan Duan
    arXiv 2023. Paper   Project  
    2023-03-22
    2023-03-22
  88. Object-Centric Slot Diffusion
    Jindong Jiang, Fei Deng, Gautam Singh, Sungjin Ahn
    arXiv 2023. Paper  
    2023-03-20
    2023-03-20
  89. Efficient Diffusion Training via Min-SNR Weighting Strategy
    Tiankai Hang, Shuyang Gu, Chen Li, Jianmin Bao, Dong Chen, Han Hu, Xin Geng, Baining Guo
    arXiv 2023. Paper  
    2023-03-16
    2023-03-16
  90. LDMVFI: Video Frame Interpolation with Latent Diffusion Models
    Duolikun Danier, Fan Zhang, David Bull
    arXiv 2023. Paper  
    2023-03-16
    2023-03-16
  91. VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation
    nknow
    CVPR 2023. Paper  
    2023-03-15
    2023-03-15
  92. Interpretable ODE-style Generative Diffusion Model via Force Field Construction
    Weiyang Jin, Yongpei Zhu, Yuxi Peng
    arXiv 2023. Paper  
    2023-03-14
    2023-03-14
  93. PARASOL: Parametric Style Control for Diffusion Image Synthesis
    Gemma Canet Tarrés, Dan Ruta, Tu Bui, John Collomosse
    arXiv 2023. Paper  
    2023-03-11
    2023-03-11
  94. Regularized Vector Quantization for Tokenized Image Synthesis
    Jiahui Zhang, Fangneng Zhan, Christian Theobalt, Shijian Lu
    arXiv 2023. Paper  
    2023-03-11
    2023-03-11
  95. Brain-Diffuser: Natural scene reconstruction from fMRI signals using generative latent diffusion
    Furkan Ozcelik, Rufin VanRullen
    arXiv 2023. Paper  
    2023-03-09
    2023-03-09
  96. Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation
    Paul Hagemann, Lars Ruthotto, Gabriele Steidl, Nicole Tianjiao Yang
    arXiv 2023. Paper  
    2023-03-08
    2023-03-08
  97. TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation
    David Berthelot, Arnaud Autef, Jierui Lin, Dian Ang Yap, Shuangfei Zhai, Siyuan Hu, Daniel Zheng, Walter Talbott, Eric Gu
    arXiv 2023. Paper  
    2023-03-07
    2023-03-07
  98. Generative Diffusions in Augmented Spaces: A Complete Recipe
    Kushagra Pandey, Stephan Mandt
    arXiv 2023. Paper  
    2023-03-03
    2023-03-03
  99. Consistency Models
    Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever
    arXiv 2023. Paper  
    2023-03-02
    2023-03-02
  100. Diffusion Probabilistic Fields
    Peiye Zhuang, Samira Abnar, Jiatao Gu, Alex Schwing, Joshua M. Susskind, Miguel Ángel Bautista
    ICLR 2023. Paper  
    2023-03-01
    2023-03-01
  101. Unsupervised Discovery of Semantic Latent Directions in Diffusion Models
    Yong-Hyun Park, Mingi Kwon, Junghyo Jo, Youngjung Uh
    arXiv 2023. Paper  
    2023-02-24
    2023-02-24
  102. Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
    Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl
    arXiv 2023. Paper   Project  
    2023-02-22
    2023-02-22
  103. Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels
    Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu
    arXiv 2023. Paper  
    2023-02-21
    2023-02-21
  104. On Calibrating Diffusion Probabilistic Models
    Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng
    arXiv 2023. Paper   Github  
    2023-02-21
    2023-02-21
  105. Learning 3D Photography Videos via Self-supervised Diffusion on Single Images
    Xiaodong Wang, Chenfei Wu, Shengming Yin, Minheng Ni, Jianfeng Wang, Linjie Li, Zhengyuan Yang, Fan Yang, Lijuan Wang, Zicheng Liu, Yuejian Fang, Nan Duan
    arXiv 2023. Paper  
    2023-02-21
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    Jaemoo Choi, Yesom Park, Myungjoo Kang
    arXiv 2023. Paper  
    2023-02-20
    2023-02-20
  107. Cross-domain Compositing with Pretrained Diffusion Models
    Roy Hachnochi, Mingrui Zhao, Nadav Orzech, Rinon Gal, Ali Mahdavi-Amiri, Daniel Cohen-Or, Amit Haim Bermano
    arXiv 2023. Paper   Github  
    2023-02-20
    2023-02-20
  108. Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent
    Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis
    arXiv 2023. Paper   Github  
    2023-02-17
    2023-02-17
  109. LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation
    Jiaxin Cheng, Xiao Liang, Xingjian Shi, Tong He, Tianjun Xiao, Mu Li
    arXiv 2023. Paper  
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    2022-05-25
    2022-05-25
  222. Flexible Diffusion Modeling of Long Videos
    William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
    arXiv 2022. Paper   Github  
    2022-05-23
    2022-05-23
  223. MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
    Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal
    NeurIPS 2022. Paper   Github  
    2022-05-19
    2022-05-19
  224. On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
    Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian
    CVPR Workshop 2022. Paper  
    2022-05-08
    2022-05-08
  225. Subspace Diffusion Generative Models
    Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi Jaakkola
    arXiv 2022. Paper   Github  
    2022-05-03
    2022-05-03
  226. Fast Sampling of Diffusion Models with Exponential Integrator
    Qinsheng Zhang, Yongxin Chen
    arXiv 2022. Paper  
    2022-04-29
    2022-04-29
  227. Semi-Parametric Neural Image Synthesis
    Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, Björn Ommer
    NeurIPS 2022. Paper  
    2022-04-25
    2022-04-25
  228. Video Diffusion Models
    Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
    NeurIPS 2022. Paper  
    2022-04-07
    2022-04-07
  229. Perception Prioritized Training of Diffusion Models
    Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim, Sungroh Yoon
    CVPR 2022. Paper   Github  
    2022-04-01
    2022-04-01
  230. Generating High Fidelity Data from Low-density Regions using Diffusion Models
    Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton Ferrer
    arXiv 2022. Paper  
    2022-03-31
    2022-03-31
  231. Diffusion Models for Counterfactual Explanations
    Guillaume Jeanneret, Loïc Simon, Frédéric Jurie
    arXiv 2022. Paper  
    2022-03-29
    2022-03-29
  232. Denoising Likelihood Score Matching for Conditional Score-based Data Generation
    Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee
    ICLR 2022. Paper  
    2022-03-27
    2022-03-27
  233. Diffusion Probabilistic Modeling for Video Generation
    Ruihan Yang, Prakhar Srivastava, Stephan Mandt
    arXiv 2022. Paper   Github  
    2022-03-16
    2022-03-16
  234. Dynamic Dual-Output Diffusion Models
    Yaniv Benny, Lior Wolf
    CVPR 2022. Paper  
    2022-03-08
    2022-03-08
  235. Conditional Simulation Using Diffusion Schrödinger Bridges
    Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet
    arXiv 2022. Paper  
    2022-02-27
    2022-02-27
  236. Diffusion Causal Models for Counterfactual Estimation
    Pedro Sanchez, Sotirios A. Tsaftaris
    PMLR 2022. Paper  
    2022-02-21
    2022-02-21
  237. Pseudo Numerical Methods for Diffusion Models on Manifolds
    Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao
    ICLR 2022. Paper   Github  
    2022-02-20
    2022-02-20
  238. Truncated Diffusion Probabilistic Models
    Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou
    arXiv 2022. Paper  
    2022-02-19
    2022-02-19
  239. Understanding DDPM Latent Codes Through Optimal Transport
    Valentin Khrulkov, Ivan Oseledets
    arXiv 2022. Paper  
    2022-02-14
    2022-02-14
  240. Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality
    Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
    ICLR 2022. Paper  
    2022-02-11
    2022-02-11
  241. Diffusion bridges vector quantized Variational AutoEncoders
    Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion, Eric Moulines
    ICML 2022. Paper  
    2022-02-10
    2022-02-10
  242. Progressive Distillation for Fast Sampling of Diffusion Models
    Tim Salimans, Jonathan Ho
    ICLR 2022. Paper  
    2022-02-01
    2022-02-01
  243. Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
    Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
    ICLR 2022. Paper  
    2022-01-17
    2022-01-17
  244. DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents
    Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar
    arXiv 2022. Paper   Github  
    2022-01-02
    2022-01-02
  245. Diffusion Autoencoders: Toward a Meaningful and Decodable Representation
    Konpat Preechakul, Nattanat Chatthee, Suttisak Wizadwongsa, Supasorn Suwajanakorn
    CVPR 2022. Paper   Project   Github  
    2021-12-30
    2021-12-30
  246. Itô-Taylor Sampling Scheme for Denoising Diffusion Probabilistic Models using Ideal Derivatives
    Hideyuki Tachibana, Mocho Go, Muneyoshi Inahara, Yotaro Katayama, Yotaro Watanabe
    arXiv 2021. Paper  
    2021-12-26
    2021-12-26
  247. High-Resolution Image Synthesis with Latent Diffusion Models
    Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer
    arXiv 2021. Paper   Github  
    2021-12-20
    2021-12-20
  248. GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
    Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
    ICML 2021. Paper   Github  
    2021-12-20
    2021-12-20
  249. Heavy-tailed denoising score matching
    Jacob Deasy, Nikola Simidjievski, Pietro Liò
    arXiv 2021. Paper  
    2021-12-17
    2021-12-17
  250. High Fidelity Visualization of What Your Self-Supervised Representation Knows About
    Florian Bordes, Randall Balestriero, Pascal Vincent
    arXiv 2021. Paper  
    2021-12-16
    2021-12-16
  251. Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
    Zhisheng Xiao, Karsten Kreis, Arash Vahdat
    arXiv 2021. Paper   Project  
    2021-12-15
    2021-12-15
  252. Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
    Tim Dockhorn, Arash Vahdat, Karsten Kreis
    ICLR 2022. Paper   Project  
    2021-12-14
    2021-12-14
  253. More Control for Free! Image Synthesis with Semantic Diffusion Guidance
    Xihui Liu, Dong Huk Park, Samaneh Azadi, Gong Zhang, Arman Chopikyan, Yuxiao Hu, Humphrey Shi, Anna Rohrbach, Trevor Darrell
    arXiv 2021. Paper  
    2021-12-10
    2021-12-10
  254. Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation
    Minghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, P.N.Suganthan
    arXiv 2021. Paper  
    2021-12-03
    2021-12-03
  255. Conditional Image Generation with Score-Based Diffusion Models
    Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
    arXiv 2021. Paper  
    2021-11-26
    2021-11-26
  256. Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
    Sam Bond-Taylor, Peter Hessey, Hiroshi Sasaki, Toby P. Breckon, Chris G. Willcocks
    arXiv 2021. Paper   Github  
    2021-11-24
    2021-11-24
  257. Diffusion Normalizing Flow
    Qinsheng Zhang, Yongxin Chen
    NeurIPS 2021. Paper   Github  
    2021-10-14
    2021-10-14
  258. Denoising Diffusion Gamma Models
    Eliya Nachmani, Robin San Roman, Lior Wolf
    arXiv 2021. Paper  
    2021-10-10
    2021-10-10
  259. Score-based Generative Neural Networks for Large-Scale Optimal Transport
    Max Daniels, Tyler Maunu, Paul Hand
    arXiv 2021. Paper  
    2021-10-07
    2021-10-07
  260. Score-Based Generative Classifiers
    Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
    arXiv 2021. Paper  
    2021-10-01
    2021-10-01
  261. Classifier-Free Diffusion Guidance
    Jonathan Ho, Tim Salimans
    NeurIPS Workshop 2021. Paper  
    2021-09-28
    2021-09-28
  262. Bilateral Denoising Diffusion Models
    Max W. Y. Lam, Jun Wang, Rongjie Huang, Dan Su, Dong Yu
    arXiv 2021. Paper   Project  
    2021-08-26
    2021-08-26
  263. ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
    Patrick Esser, Robin Rombach, Andreas Blattmann, Björn Ommer
    NeurIPS 2021. Paper   Project  
    2021-08-19
    2021-08-19
  264. ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
    Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, Sungroh Yoon
    ICCV 2021 (Oral). Paper   Github  
    2021-08-06
    2021-08-06
  265. SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
    Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon
    ICLR 2022. Paper   Project   Github  
    2021-08-02
    2021-08-02
  266. Structured Denoising Diffusion Models in Discrete State-Spaces
    Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
    NeurIPS 2021. Paper  
    2021-07-07
    2021-07-07
  267. Variational Diffusion Models
    Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
    arXiv 2021. Paper   Github  
    2021-07-01
    2021-07-01
  268. Diffusion Priors In Variational Autoencoders
    Antoine Wehenkel, Gilles Louppe
    ICML Workshop 2021. Paper  
    2021-06-29
    2021-06-29
  269. Deep Generative Learning via Schrödinger Bridge
    Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
    ICML 2021. Paper  
    2021-06-19
    2021-06-19
  270. Non Gaussian Denoising Diffusion Models
    Eliya Nachmani, Robin San Roman, Lior Wolf
    arXiv 2021. Paper   Project  
    2021-06-14
    2021-06-14
  271. D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
    Abhishek Sinha, Jiaming Song, Chenlin Meng, Stefano Ermon
    NeurIPS 2021. Paper   Project   Github  
    2021-06-12
    2021-06-12
  272. Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
    Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
    ICML 2022. Paper  
    2021-06-10
    2021-06-10
  273. Score-based Generative Modeling in Latent Space
    Arash Vahdat, Karsten Kreis, Jan Kautz
    arXiv 2021. Paper  
    2021-06-10
    2021-06-10
  274. Learning to Efficiently Sample from Diffusion Probabilistic Models
    Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
    arXiv 2021. Paper  
    2021-06-07
    2021-06-07
  275. A Variational Perspective on Diffusion-Based Generative Models and Score Matching
    Chin-Wei Huang, Jae Hyun Lim, Aaron Courville
    NeurIPS 2021. Paper   Github  
    2021-06-05
    2021-06-05
  276. Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
    Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet
    arXiv 2021. Paper   Project   Github  
    2021-06-01
    2021-06-01
  277. On Fast Sampling of Diffusion Probabilistic Models
    Zhifeng Kong, Wei Ping
    ICML Workshop 2021. Paper   Github  
    2021-05-31
    2021-05-31
  278. Cascaded Diffusion Models for High Fidelity Image Generation
    Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
    JMLR 2021. Paper   Project  
    2021-05-30
    2021-05-30
  279. Gotta Go Fast When Generating Data with Score-Based Models
    Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas
    arXiv 2021. Paper   Github  
    2021-05-28
    2021-05-28
  280. Diffusion Models Beat GANs on Image Synthesis
    Prafulla Dhariwal, Alex Nichol
    arXiv 2021. Paper   Github  
    2021-05-11
    2021-05-11
  281. Image Super-Resolution via Iterative Refinement
    Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
    arXiv 2021. Paper   Project   Github  
    2021-04-15
    2021-04-15
  282. Noise Estimation for Generative Diffusion Models
    Robin San-Roman, Eliya Nachmani, Lior Wolf
    arXiv 2021. Paper  
    2021-04-06
    2021-04-06
  283. Improved Denoising Diffusion Probabilistic Models
    Alex Nichol, Prafulla Dhariwal
    ICLR 2021. Paper   Github  
    2021-02-18
    2021-02-18
  284. Maximum Likelihood Training of Score-Based Diffusion Models
    Yang Song, Conor Durkan, Iain Murray, Stefano Ermon
    arXiv 2021. Paper  
    2021-01-22
    2021-01-22
  285. Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed
    Eric Luhman, Troy Luhman
    arXiv 2021. Paper   Github  
    2021-01-07
    2021-01-07
  286. Learning Energy-Based Models by Diffusion Recovery Likelihood
    Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma
    ICLR 2021. Paper   Github  
    2020-12-15
    2020-12-15
  287. Score-Based Generative Modeling through Stochastic Differential Equations
    Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole
    ICLR 2021 (Oral). Paper   Github  
    2020-11-26
    2020-11-26
  288. Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
    Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
    ICML 2021. Paper  
    2020-10-16
    2020-10-16
  289. Denoising Diffusion Implicit Models*
    Jiaming Song, Chenlin Meng, Stefano Ermon
    ICLR 2021. Paper   Github  
    2020-10-06
    2020-10-06
  290. Adversarial score matching and improved sampling for image generation
    Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Rémi Tachet des Combes, Ioannis Mitliagkas
    ICLR 2021. Paper   Github  
    2020-09-11
    2020-09-11
  291. Denoising Diffusion Probabilistic Models
    Jonathan Ho, Ajay Jain, Pieter Abbeel
    NeurIPS 2020. Paper   Github   Github2  
    2020-06-19
    2020-06-19
  292. Improved Techniques for Training Score-Based Generative Models
    Yang Song, Stefano Ermon
    NeurIPS 2020. Paper   Github  
    2020-06-16
    2020-06-16
  293. Generative Modeling by Estimating Gradients of the Data Distribution
    Yang Song, Stefano Ermon
    NeurIPS 2019. Paper   Project   Github  
    2019-07-12
    2019-07-12
  294. Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
    Belinda Tzen, Maxim Raginsky
    arXiv 2019. Paper  
    2019-05-23
    2019-05-23
  295. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
    Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli
    ICML 2015. Paper   Github  
    2015-03-02
    2015-03-02
Counts - 295   Back to top