% Key papers for Large-scale GAN latent analysis (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_analyzing_15145,
  title = {{Analyzing and Improving the Image Quality of StyleGAN}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2019_large_28756,
  title = {{Large Scale GAN Training for High Fidelity Natural Image Synthesis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/937},
}

@inproceedings{icml2016_generative_35853,
  title = {{Generative Adversarial Text to Image Synthesis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/reed16.html},
}

@inproceedings{cvpr2020_interpreting_15706,
  title = {{Interpreting the Latent Space of GANs for Semantic Face Editing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2021_alias_62118,
  title = {{Alias-Free Generative Adversarial Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27390},
}

@inproceedings{cvpr2019_dm_14002,
  title = {{DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_deformable_12996,
  title = {{Deformable GANs for Pose-Based Human Image Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Siarohin_Deformable_GANs_for_CVPR_2018_paper.html},
}

@inproceedings{cvpr2021_closed_16703,
  title = {{Closed-Form Factorization of Latent Semantics in GANs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2017_stacked_12663,
  title = {{Stacked Generative Adversarial Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2023_scaling_22131,
  title = {{Scaling Up GANs for Text-to-Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22519},
}

@inproceedings{neurips2019_large_58457,
  title = {{Large Scale Adversarial Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14063},
}

@inproceedings{cvpr2018_sketchygan_13595,
  title = {{SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Chen_SketchyGAN_Towards_Diverse_CVPR_2018_paper.html},
}

@inproceedings{cvpr2020_image_15672,
  title = {{Image Processing Using Multi-Code GAN Prior}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2019_clustergan_101670,
  title = {{ClusterGAN: Latent Space Clustering in Generative Adversarial Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4385},
}

@inproceedings{cvpr2019_object_14594,
  title = {{Object-Driven Text-To-Image Synthesis via Adversarial Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2022_df_18574,
  title = {{DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_adversarial_15130,
  title = {{Adversarial Latent Autoencoders}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2022_styleswin_19953,
  title = {{StyleSwin: Transformer-Based GAN for High-Resolution Image Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{neurips2016_learning_55831,
  title = {{Learning What and Where to Draw}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7407},
}

@inproceedings{iclr2017_lr_28257,
  title = {{LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=HJ1kmv9xx},
}

@inproceedings{aaai2024_procedural_6997,
  title = {{Procedural Level Generation with Diffusion Models from a Single Example}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28865},
}

@inproceedings{cvpr2025_exploring_26192,
  title = {{Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33020},
}

@inproceedings{cvpr2025_style_27768,
  title = {{Style Quantization for Data-Efficient GAN Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32719},
}

@inproceedings{icml2024_e_45254,
  title = {{E\$^2\$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33198},
}

@inproceedings{icml2026_scalable_53045,
  title = {{Scalable GANs with Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=bTfHzEx9Xk},
}

@inproceedings{iclr2025_adversarial_83750,
  title = {{Adversarial Generative Flow Network for Solving Vehicle Routing Problems}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28069},
}