uai 2021 v0

Author: minimrbanana

MOMoGP.py

@@ -1,2 +1,50 @@
 # MOMoGP
-Code for "Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression" @UAI2021
+
+This is the official repository for MOMoGP introduced in 
+[Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression](https://ml-research.github.io/papers/yu2021uai_momogps.pdf) by Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, and Kristian Kersting, to be published at UAI 2021.
+
+![Learn_MOMoGP](./figures/Learn_MOMoGP.png)
+
+
+## Setup
+
+This will clone the repo, install a Python virtual env (requires Python 3.6), the required packages, and will download some datasets.
+
+    git clone https://github.com/minimrbanana/MOMoGP
+    ./setup.sh
+
+## Demos
+
+To illustrate the usage of the code:
+
+    source ./venv_momogp/bin/activate
+    python run_MOMoGP.py --data=parkinsons
+
+"parkinsons" can be replaced with "scm20d" or "wind" or "energy" or "usflight".
+
+### Hyperparameters
+
+If not specified, the corresponding hyperparameters are set by default values.
+If train on CPU, use:
+
+    python run_MOMoGP.py --data=parkinsons --cpu
+
+## Citation
+If you find this code useful in your research, please consider citing:
+
+
+    @inproceedings{yu2021uai_momogps,
+      title = {Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression},
+      author = {Yu, Zhongjie and Zhu, Mingye and Trapp, Martin and Skryagin, Arseny and Kersting, Kristian},
+      booktitle = {Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI)},
+      year = {2021}
+    }
+
+## Acknowledgments
+
+* This work is supported by the Federal Ministry of Education and Research (BMBF; project "MADESI", FKZ 01IS18043B, and Competence Center for AI and Labour; "kompAKI", FKZ 02L19C150), the Hessian Ministry of Higher Education, Research, Science and the Arts (HMWK; projects "The Third Wave of AI" and "The Adaptive Mind"), the Hessian research priority programme LOEWE within the project "WhiteBox", and the National Research Center for Applied Cybersecurity ATHENE, a joint effort of BMBF and HMWK. M.T. acknowledges funding from the Academy of Finland (grant number 324345).
+
+* The code is developed based on the Python implementation of DSMGP from [Eugene](https://github.com/eugene/spngp).
+
+
+