Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Feb 05, 2022 1 min read

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

This is the official implementation of the following paper accepted to AISTATS 2022:

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Yeshu Li, Zhan Shi, Xinhua Zhang, Brian D. Ziebart

[Proceeding link TBA]

Requirements

numpy
scipy

Quick Start

Run

python main.py

Citation

Please cite our work if you find it useful in your research:

(to do: bibtex info)

Acknowledgement

This project is based upon work supported by the National Science Foundation under Grant No. 1652530.

GitHub

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John was the first writer to have joined pythonawesome.com. He has since then inculcated very effective writing and reviewing culture at pythonawesome which rivals have found impossible to imitate.

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Requirements

Quick Start

Citation

Acknowledgement

GitHub

John

VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

This project has been designed to take monitoring data from Voltronic, Axpert, Mppsolar PIP, Voltacon, Effekta

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

Requirements

Quick Start

Citation

Acknowledgement

GitHub

VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

This project has been designed to take monitoring data from Voltronic, Axpert, Mppsolar PIP, Voltacon, Effekta

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