csbm

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Categorical Schrödinger Bridge Matching (CSBM)

Grigoriy Ksenofontov, Alexander Korotin

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This repository hosts the official checkpoints for the paper "Categorical Schrödinger Bridge Matching", accepted at ICML 2025.

📌 TL;DR

This paper extends the Schrödinger Bridge problem to work with discrete time and spaces.

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💾 Checkpoints

CSBM

[!NOTE] Each experiment directory includes a config.yaml file with the full training configuration.

Additional Components

1. vqgan_celeba_f8_1024.ckpt — VQ-GAN pretrained on the CelebA dataset
2. tokenizer_amazon.json — Tokenizer trained on the Amazon Reviews dataset

🎓 Citation

@inproceedings{
  ksenofontov2025categorical,
  title={Categorical {Schr\"odinger} Bridge Matching},
  author={Grigoriy Ksenofontov and Alexander Korotin},
  booktitle={Forty-second International Conference on Machine Learning},
  year={2025},
  url={https://openreview.net/forum?id=RBly0nOr2h}
}

🙏 Credits

• Weights & Biases — experiment-tracking and visualization toolkit;
• Hugging Face — Tokenizers and Accelerate libraries for tokenizer implementation, parallel training, and checkpoint hosting on the Hub;
• D3PM — reference implementation of discrete-diffusion models;
• Taming Transformers — original VQ-GAN codebase;
• VQ-Diffusion — vector-quantized diffusion architecture;
• MDLM — diffusion architecture for text-generation experiments;
• ASBM — evaluation metrics and baseline models for CelebA face transfer;
• Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoising — processed Amazon Reviews dataset and sentiment-transfer baselines;
• Inkscape — an excellent open-source editor for vector graphics.