mlsanityData to 7 Oct 2026

Denoising Diffusion Gamma Models

arXiv 2110.05948 ↗First posted 10 Oct 2021eess.SP cs.AI cs.CVcited by 27

On the map: Diffusion models → Diffusion foundations and sampling

Abstract (arXiv)

Generative diffusion processes are an emerging and effective tool for image and speech generation. In the existing methods, the underlying noise distribution of the diffusion process is Gaussian noise. However, fitting distributions with more degrees of freedom could improve the performance of such generative models. In this work, we investigate other types of noise distribution for the diffusion process. Specifically, we introduce the Denoising Diffusion Gamma Model (DDGM) and show that noise from Gamma distribution provides improved results for image and speech generation. Our approach preserves the ability to efficiently sample state in the training diffusion process while using Gamma noise.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 30 of its 38 references that are in the map. First posted on arXiv 10 Oct 2021.

Builds on

30 of 38 references.

Closest ancestors · 11

Same direction, newest first

  1. 2021Bilateral Denoising Diffusion Models26 Aug
  2. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models6 Aug
  3. 2021Structured Denoising Diffusion Models in Discrete State-Spaces7 Jul
  4. 2021Variational Diffusion Models1 Jul
  5. 2021Learning to Efficiently Sample from Diffusion Probabilistic Models7 Jun
  6. 2021A Variational Perspective on Diffusion-Based Generative Models and Score Matching5 Jun
  7. 2021On Fast Sampling of Diffusion Probabilistic Models31 May
  8. 2021Diffusion Models Beat GANs on Image Synthesis11 May
  9. 2020Score-Based Generative Modeling through Stochastic Differential Equations26 Nov
  10. 2020Denoising Diffusion Implicit Models6 Oct
  11. 2020Denoising Diffusion Probabilistic Models19 Jun

Other references · 19

  1. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  2. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  3. 2013Auto-Encoding Variational Bayescited by 3,980
  4. 2014Deep Learning Face Attributes in the Wildcited by 3,679
  5. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  6. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  7. 2016WaveNet: A Generative Model for Raw Audiocited by 1,710
  8. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
  9. 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,376
  10. 2015LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loopcited by 1,350
  11. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  12. 2020NVAE: A Deep Hierarchical Variational Autoencodercited by 635
7 more
  1. 2020WaveGrad: Estimating Gradients for Waveform Generationcited by 620
  2. 2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 445
  3. 2016A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluationcited by 236
  4. 2018Adversarial Audio Synthesiscited by 222
  5. 2018Efficient Neural Audio Synthesiscited by 218
  6. 2020Learning Energy-Based Models by Diffusion Recovery Likelihoodcited by 122
  7. 2019High Fidelity Speech Synthesis with Adversarial Networkscited by 90

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 8; 2024: 2; 2025: 7; 2026: 4.

27 papers.

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  1. 2022MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolationcited by 307
  2. 2023Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restorationcited by 164
  3. 2022Soft Diffusion: Score Matching for General Corruptionscited by 101
  4. 2023A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AIcited by 68
  5. 2023On the Design Fundamentals of Diffusion Models: A Surveycited by 59
  6. 2023Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistentcited by 58
  7. 2022Efficient Diffusion Models for Vision: A Surveycited by 50
  8. 2023Iterative α-(de)Blending: a Minimalist Deterministic Diffusion Modelcited by 46
  9. 2022Maximum Likelihood Training of Implicit Nonlinear Diffusion Modelscited by 42
  10. 2024Diffusion Models for Audio Restorationcited by 32
  11. 2022Dynamic Dual-Output Diffusion Modelscited by 25
  12. 2025Variational Control for Guidance in Diffusion Modelscited by 22
15 more
  1. 2022Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Modelscited by 17
  2. 2024Heavy-Tailed Diffusion with Denoising L'evy Probabilistic Modelscited by 16
  3. 2023DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistencycited by 14
  4. 2023Star-Shaped Denoising Diffusion Probabilistic Modelscited by 13
  5. 2025FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Computecited by 12
  6. 2025Generative modelling with jump-diffusionscited by 4
  7. 2026Diffusion Models with Heavy-Tailed Targets: Score Estimation and Sampling Guaranteescited by 4
  8. 2023DiffLoad: Uncertainty Quantification in Electrical Load Forecasting with the Diffusion Modelcited by 3
  9. 2025Dale meets Langevin: A Multiplicative Denoising Diffusion Modelcited by 2
  10. 2025GARD: Gamma-based Anatomical Restoration and Denoising for Retinal OCTcited by 1
  11. 2026Exploiting Intermediate Reconstructions in Optical Coherence Tomography for Test-Time Adaption of Medical Image Segmentationcited by 1
  12. 2025VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distributioncited by 0
  13. 2025Diffusion Models under Alternative Noise: Simplified Analysis and Sensitivitycited by 0
  14. 2026Region-Adaptive Generative Compression with Spatially Varying Diffusion Modelscited by 0
  15. 2026γ-Bridge: A Look-Parametric Diffusion Bridgecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2021Non Gaussian Denoising Diffusion Models
  2. 2023Diffusion Model for Generative Image Denoising
  3. 2021Noise Estimation for Generative Diffusion Models
  4. 2022Diffusion Models in Vision: A Survey
  5. 2023Diffusion models with location-scale noise
  6. 2022Speech Enhancement and Dereverberation with Diffusion-based Generative Models
  7. 2022Accelerating Diffusion Models via Early Stop of the Diffusion Process
  8. 2024GUD: Generation with Unified Diffusion