| PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher | ✓ Link | 0.79 | | | PaGoDA | 2024-05-23 |
| StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets | ✓ Link | 1.10 | | | StyleGAN-XL | 2022-02-01 |
| The GAN is dead; long live the GAN! A Modern GAN Baseline | ✓ Link | 1.27 | | | R3GAN | 2025-01-09 |
| Input Perturbation Reduces Exposure Bias in Diffusion Models | ✓ Link | 2.66 | | | DDPM-IP | 2023-01-27 |
| Flow Matching for Generative Modeling | ✓ Link | 5.02 | 3.53 | | FM | 2022-10-06 |
| Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking | | 6.98 | | 11.65 | MDM-Prime | 2025-05-24 |
| Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking | | 7.91 | | 11.60 | MDM | 2025-05-24 |
| Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation | ✓ Link | 8.42 | 3.85 | 11.82 | DDPM++ (VP, NLL) + ST | 2021-06-10 |
| Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs | ✓ Link | 9.09 | 3.43 | | i-DODE | 2023-05-06 |
| Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game | ✓ Link | 12.3 | | | MSGAN | 2019-11-16 |
| Denoising Diffusion Probabilistic Models | ✓ Link | 16.18 | 3.89 | | DDPM | 2020-06-19 |
| Neural Diffusion Models | | 17.02 | 3.55 | | NDM | 2023-10-12 |
| On Investigating the Conservative Property of Score-Based Generative Models | ✓ Link | 19.62 | | 9.94 | QC-NCSN++ | 2022-09-26 |
| Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling | ✓ Link | | 3.34 | | NFDM | 2024-04-19 |
| Generative Modeling with Bayesian Sample Inference | ✓ Link | | 3.44 | | BSI | 2025-02-11 |
| Densely connected normalizing flows | ✓ Link | | 3.63 | | DenseFlow-74-10 | 2021-06-08 |
| Variational Diffusion Models | ✓ Link | | 3.72 | | VDM | 2021-07-01 |
| Hierarchical Transformers Are More Efficient Language Models | ✓ Link | | 3.74 | | Hourglass | 2021-10-26 |
| Reflected Diffusion Models | ✓ Link | | 3.74 | | Reflected Diffusion | 2023-04-10 |
| Maximum Likelihood Training of Score-Based Diffusion Models | ✓ Link | | 3.76 | | ScoreFlow | 2021-01-22 |
| Image Transformer | | | 3.77 | | Image Transformer | 2018-02-15 |
| Preventing Posterior Collapse with delta-VAEs | | | 3.77 | | δ-VAE | 2019-01-10 |
| Multi-Resolution Continuous Normalizing Flows | ✓ Link | | 3.77 | | MRCNF | 2021-06-15 |
| Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images | ✓ Link | | 3.8 | | Very Deep VAE | 2020-11-20 |
| Conditional Image Generation with PixelCNN Decoders | ✓ Link | | 3.83 | | Gated PixelCNN | 2016-06-16 |
| Generating High Fidelity Images with Subscale Pixel Networks and Multidimensional Upscaling | | | 3.85 | | SPN Menick and Kalchbrenner (2019) | 2018-12-04 |
| Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design | ✓ Link | | 3.86 | | Flow++ | 2019-02-01 |
| Pixel Recurrent Neural Networks | ✓ Link | | 3.86 | | PixelRNN | 2016-01-25 |
| NVAE: A Deep Hierarchical Variational Autoencoder | ✓ Link | | 3.92 | | NVAE w/ flow | 2020-07-08 |
| Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models | ✓ Link | | 3.92 | | ANF Huang et al. (2020) | 2020-02-17 |
| BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling | ✓ Link | | 3.96 | | BIVA Maaloe et al. (2019) | 2019-02-06 |
| Residual Flows for Invertible Generative Modeling | ✓ Link | | 4.01 | | Residual Flow | 2019-06-06 |
| MintNet: Building Invertible Neural Networks with Masked Convolutions | ✓ Link | | 4.06 | | MintNet | 2019-07-18 |
| Glow: Generative Flow with Invertible 1x1 Convolutions | ✓ Link | | 4.09 | | Glow (Kingma and Dhariwal, 2018) | 2018-07-09 |
| Density estimation using Real NVP | ✓ Link | | 4.28 | | Real NVP (Dinh et al., 2017) | 2016-05-27 |