Merge remote-tracking branch 'origin/master'

LICENSE

@@ -0,0 +1,29 @@
+BSD 3-Clause License
+
+Copyright (c) 2020, Antoine Wehenkel
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

README.md

@@ -69,3 +69,18 @@ are located in the folder models/UMNN.
 the net but to the price of a higher memory cost. 
 - `UMNNMAF.py` contains the implementation of the different networks required by UMNN.
 - `UMNNMAFFlow.py` contains the implementation of flows made of UMNNs.
+- Check [here](https://github.com/AWehenkel/generalized-UMNN/) if you are interested by modeling functions that are monotonic with respect to more than one input variable. (Do not hesitate to contact me for more details)
+
+## Cite
+
+If you make use of this code in your own work, please cite our paper:
+
+```
+@inproceedings{wehenkel2019unconstrained,
+  title={Unconstrained monotonic neural networks},
+  author={Wehenkel, Antoine and Louppe, Gilles},
+  booktitle={Advances in Neural Information Processing Systems},
+  pages={1543--1553},
+  year={2019}
+}
+```