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README.md

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-# DDPM
-PyTorch DDPM implementation
+## Denoising Diffusion Probabilistic Models
+An implementation of Denoising Diffusion Probabilistic Models for class-conditional image generation written in PyTorch.
+
+## Experiments on MNIST
+
+TODO
+
+## Acknowledgements
+
+I used [Phil Wang's implementation](https://github.com/lucidrains/denoising-diffusion-pytorch) as a reference for my work.
+
+## Citations
+
+```bibtex
+@misc{ho2020denoising,
+    title   = {Denoising Diffusion Probabilistic Models},
+    author  = {Jonathan Ho and Ajay Jain and Pieter Abbeel},
+    year    = {2020},
+    eprint  = {2006.11239},
+    archivePrefix = {arXiv},
+    primaryClass = {cs.LG}
+}
+```
+
+```bibtex
+@inproceedings{anonymous2021improved,
+    title   = {Improved Denoising Diffusion Probabilistic Models},
+    author  = {Anonymous},
+    booktitle = {Submitted to International Conference on Learning Representations},
+    year    = {2021},
+    url     = {https://openreview.net/forum?id=-NEXDKk8gZ},
+    note    = {under review}
+}