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README.md

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 ### Updates 
 * [Discard experiments directory.](https://github.com/kaanguney/normalizing_flows/tree/main/notebooks/experiments)
-* [Preprocessing currently supports `prostate.xls`.](https://github.com/kaanguney/normalizing_flows/tree/main/scripts/preprocessing)
-* [Refer to noisy-moons directory]() for the most recent, most visual implementation.
+* [Pre-processing](https://github.com/kaanguney/normalizing_flows/tree/main/scripts/preprocessing) currently supports a dataset called `prostate.xls`. 
+* [Refer to noisy-moons directory](https://github.com/kaanguney/normalizing_flows/tree/main/noisy-moons) for the most recent implementations; incl. visuals.
 
 ### References
 * Rezende, D. J., & Mohamed, S. (2015). [Variational Inference with Normalizing Flows.](https://arxiv.org/abs/1505.05770v6)
 * Kobyzev, I., Prince, S. J. D., & Brubaker, M. A. (2019). [Normalizing Flows: An Introduction and Review of Current Methods.](https://arxiv.org/abs/1908.09257v4)
 * [Probabilistic Deep Learning with TensorFlow 2 by Imperial College London](https://www.coursera.org/learn/probabilistic-deep-learning-with-tensorflow2)
 * Blog posts
- * [Eric Jang](https://github.com/ericjang/normalizing-flows-tutorial)
- * [Lilian Weng](https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html)
+  * [Eric Jang](https://github.com/ericjang/normalizing-flows-tutorial)
+  * [Lilian Weng](https://lilianweng.github.io/lil-log/2018/10/13/flow-based-deep-generative-models.html)
 * [TensorFlow Probability](https://www.tensorflow.org/probability)