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Learning to Efficiently Sample from Diffusion Probabilistic Models

Learning to Efficiently Sample from Diffusion Probabilistic Models

7 June 2021
Daniel Watson
Jonathan Ho
Mohammad Norouzi
William Chan
    DiffM
ArXivPDFHTML

Papers citing "Learning to Efficiently Sample from Diffusion Probabilistic Models"

39 / 39 papers shown
Title
Generative Modelling with High-Order Langevin Dynamics
Generative Modelling with High-Order Langevin Dynamics
Ziqiang Shi
Rujie Liu
DiffM
62
2
0
03 Jan 2025
Mixture of Efficient Diffusion Experts Through Automatic Interval and
  Sub-Network Selection
Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection
Alireza Ganjdanesh
Yan Kang
Yuchen Liu
Richard Y. Zhang
Zhe Lin
Heng Huang
DiffM
34
2
0
23 Sep 2024
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
Alireza Ganjdanesh
Reza Shirkavand
Shangqian Gao
Heng Huang
DiffM
VLM
56
4
0
17 Jun 2024
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
En-hao Liu
Junyi Zhu
Zinan Lin
Xuefei Ning
Shuaiqi Wang
...
Sergey Yekhanin
Guohao Dai
Huazhong Yang
Yu-Xiang Wang
Yu Wang
MoMe
57
4
0
02 Apr 2024
Purify++: Improving Diffusion-Purification with Advanced Diffusion
  Models and Control of Randomness
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness
Boya Zhang
Weijian Luo
Zhihua Zhang
34
10
0
28 Oct 2023
Towards More Accurate Diffusion Model Acceleration with A Timestep
  Aligner
Towards More Accurate Diffusion Model Acceleration with A Timestep Aligner
Mengfei Xia
Yujun Shen
Changsong Lei
Yu Zhou
Ran Yi
Deli Zhao
Wenping Wang
Yong-jin Liu
24
5
0
14 Oct 2023
Efficient Integrators for Diffusion Generative Models
Efficient Integrators for Diffusion Generative Models
Kushagra Pandey
Maja R. Rudolph
Stephan Mandt
DiffM
21
10
0
11 Oct 2023
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Suttisak Wizadwongsa
Worameth Chinchuthakun
Pramook Khungurn
Amit Raj
Supasorn Suwajanakorn
DiffM
48
2
0
20 Jul 2023
PTQD: Accurate Post-Training Quantization for Diffusion Models
PTQD: Accurate Post-Training Quantization for Diffusion Models
Yefei He
Luping Liu
Jing Liu
Weijia Wu
Hong Zhou
Bohan Zhuang
DiffM
MQ
30
103
0
18 May 2023
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural
  Network for Spatio-temporal Forecasting
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting
G. Liang
Prayag Tiwari
Sławomir Nowaczyk
Stefan Byttner
F. Alonso-Fernandez
DiffM
39
12
0
16 May 2023
Towards Real-time Text-driven Image Manipulation with Unconditional
  Diffusion Models
Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models
Nikita Starodubcev
Dmitry Baranchuk
Valentin Khrulkov
Artem Babenko
DiffM
49
4
0
10 Apr 2023
A Comprehensive Survey of AI-Generated Content (AIGC): A History of
  Generative AI from GAN to ChatGPT
A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT
Yihan Cao
Siyu Li
Yixin Liu
Zhiling Yan
Yutong Dai
Philip S. Yu
Lichao Sun
29
507
0
07 Mar 2023
Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
Suttisak Wizadwongsa
Supasorn Suwajanakorn
DiffM
40
12
0
27 Jan 2023
Fast Inference in Denoising Diffusion Models via MMD Finetuning
Fast Inference in Denoising Diffusion Models via MMD Finetuning
Emanuele Aiello
D. Valsesia
E. Magli
DiffM
22
4
0
19 Jan 2023
Post-training Quantization on Diffusion Models
Post-training Quantization on Diffusion Models
Yuzhang Shang
Zhihang Yuan
Bin Xie
Bingzhe Wu
Yan Yan
DiffM
MQ
15
159
0
28 Nov 2022
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion
  Models
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
Muyang Li
Ji Lin
Chenlin Meng
Stefano Ermon
Song Han
Jun-Yan Zhu
DiffM
37
45
0
03 Nov 2022
LION: Latent Point Diffusion Models for 3D Shape Generation
LION: Latent Point Diffusion Models for 3D Shape Generation
Fangyin Wei
Arash Vahdat
Francis Williams
Zan Gojcic
Or Litany
Sanja Fidler
Karsten Kreis
DiffM
49
485
0
12 Oct 2022
GENIE: Higher-Order Denoising Diffusion Solvers
GENIE: Higher-Order Denoising Diffusion Solvers
Tim Dockhorn
Arash Vahdat
Karsten Kreis
DiffM
49
104
0
11 Oct 2022
Efficient Diffusion Models for Vision: A Survey
Efficient Diffusion Models for Vision: A Survey
Anwaar Ulhaq
Naveed Akhtar
MedIm
32
60
0
07 Oct 2022
OCD: Learning to Overfit with Conditional Diffusion Models
OCD: Learning to Overfit with Conditional Diffusion Models
Shahar Lutati
Lior Wolf
DiffM
20
8
0
02 Oct 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Bin Cui
Ming-Hsuan Yang
DiffM
MedIm
224
1,304
0
02 Sep 2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for
  Inverse Problems
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems
Giannis Daras
Y. Dagan
A. Dimakis
C. Daskalakis
BDL
31
15
0
18 Jun 2022
Lossy Compression with Gaussian Diffusion
Lossy Compression with Gaussian Diffusion
Lucas Theis
Tim Salimans
Matthew D. Hoffman
Fabian Mentzer
DiffM
28
77
0
17 Jun 2022
Estimating the Optimal Covariance with Imperfect Mean in Diffusion
  Probabilistic Models
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models
Fan Bao
Chongxuan Li
Jiacheng Sun
Jun Zhu
Bo Zhang
DiffM
30
72
0
15 Jun 2022
gDDIM: Generalized denoising diffusion implicit models
gDDIM: Generalized denoising diffusion implicit models
Qinsheng Zhang
Molei Tao
Yongxin Chen
DiffM
34
112
0
11 Jun 2022
How Much is Enough? A Study on Diffusion Times in Score-based Generative
  Models
How Much is Enough? A Study on Diffusion Times in Score-based Generative Models
Giulio Franzese
Simone Rossi
Lixuan Yang
A. Finamore
Dario Rossi
Maurizio Filippone
Pietro Michiardi
DiffM
13
46
0
10 Jun 2022
Few-Shot Diffusion Models
Few-Shot Diffusion Models
Giorgio Giannone
Didrik Nielsen
Ole Winther
DiffM
183
49
0
30 May 2022
Fast Sampling of Diffusion Models with Exponential Integrator
Fast Sampling of Diffusion Models with Exponential Integrator
Qinsheng Zhang
Yongxin Chen
DiffM
22
415
0
29 Apr 2022
Generating High Fidelity Data from Low-density Regions using Diffusion
  Models
Generating High Fidelity Data from Low-density Regions using Diffusion Models
Vikash Sehwag
C. Hazirbas
Albert Gordo
Firat Ozgenel
Cristian Canton Ferrer
DiffM
33
66
0
31 Mar 2022
Diffusion Models for Counterfactual Explanations
Diffusion Models for Counterfactual Explanations
Guillaume Jeanneret
Loïc Simon
F. Jurie
DiffM
32
55
0
29 Mar 2022
Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion
Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion
Tianpei Gu
Guangyi Chen
Junlong Li
Chunze Lin
Yongming Rao
Jie Zhou
Jiwen Lu
DiffM
VGen
34
194
0
25 Mar 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality
  Speech Synthesis
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis
Max W. Y. Lam
Jun Wang
Dan Su
Dong Yu
DiffM
34
92
0
25 Mar 2022
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in
  Diffusion Probabilistic Models
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
Fan Bao
Chongxuan Li
Jun Zhu
Bo Zhang
DiffM
54
337
0
17 Jan 2022
Quasi-Taylor Samplers for Diffusion Generative Models based on Ideal
  Derivatives
Quasi-Taylor Samplers for Diffusion Generative Models based on Ideal Derivatives
Hideyuki Tachibana
Mocho Go
Muneyoshi Inahara
Yotaro Katayama
Yotaro Watanabe
DiffM
27
3
0
26 Dec 2021
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models
  for Inverse Problems through Stochastic Contraction
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung
Byeongsu Sim
Jong Chul Ye
MedIm
DiffM
36
342
0
09 Dec 2021
Deblurring via Stochastic Refinement
Deblurring via Stochastic Refinement
Jay Whang
M. Delbracio
Hossein Talebi
Chitwan Saharia
A. Dimakis
P. Milanfar
DiffM
33
265
0
05 Dec 2021
A Survey on Neural Speech Synthesis
A Survey on Neural Speech Synthesis
Xu Tan
Tao Qin
Frank Soong
Tie-Yan Liu
AI4TS
18
352
0
29 Jun 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
41
480
0
08 Mar 2021
Efficient Content-Based Sparse Attention with Routing Transformers
Efficient Content-Based Sparse Attention with Routing Transformers
Aurko Roy
M. Saffar
Ashish Vaswani
David Grangier
MoE
243
580
0
12 Mar 2020
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