## Rectified Factor Networks

Rectified Factor Networks (RFNs) are an unsupervised technique that learns a non-linear, high-dimensional representation of its input. The underlying algorithm has been published in Rectified Factor Networks, Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter, NIPS 2015.
**Code:**

- GitHub repository: librfn code for Python
- GitHub repository: librfn code for C++
- GitHub repository: librfn code for R

**Paper, supplement and manual:**

- Paper.pdf: NIPS paper, Rectified Factor Networks
- Supplement.pdf: Supplement, providing mathematical properties (theorems & proofs)