NeuPI: A Library for Neural Probabilistic Inference
Arya, Shivvrat; Rahman, Tahrima; Gogate, Vibhav;
NeuPI: A Library for Neural Probabilistic Inference
NeuPI is a PyTorch-based library for solving inference tasks in Probabilistic Models using neural network surrogates. It provides a modular framework for training neural models in a self-supervised fashion, where the Probabilistic Model itself provides the supervisory signal.
If you use this software, please cite it as below.
machine learning, probabilistic graphical models, pytorch, probabilistic inference, neural networks
machine learning, probabilistic graphical models, pytorch, probabilistic inference, neural networks
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
Average
Average
Average