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Adaptive G-UKT: a unified probabilistic framework for knowledge tracing via adaptive graph topology learning and uncertainty-aware Gaussian embeddings. [PDF]
Sci RepJia N, Su W, Xian J, Zou S, Xia Y.
europepmc +1 more source
An Uncertainty-Aware Temporal Transformer for Probabilistic Interval Modeling in Wind Power Forecasting. [PDF]
Sensors (Basel)Sun S +6 more
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Probabilistic graphical models [PDF]
Wiley Series in Probability and Statistics, 2014 This report presents probabilistic graphical models that are based on imprecise probabilities using a simplified language. In particular the discussion is focused on credal networks and discrete domains. It describes the building blocks of credal networks algorithms to perform inference and discusses on complexity results and related work.
Alessandro Antonucci +2 more
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Probabilistic Graphical Models [PDF]
Advances in Computer Vision and Pattern Recognition, 2015 In this chapter, we will briefly summarize the basic concepts of probability as well as graph theory.We start with important terms and definitions from graph theory and emphasize the relation to our hierarchical models. Directed and undirected graphs will be introduced and compared with each other. Then, we will give an overview of the random variables
Luis Enrique Sucar
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Probabilistic Graphical Models
Advances in Computer Vision and Pattern Recognition, 2021“He who ignores the law of probabilities challenges an adversary that is seldom beaten.” – Ambrose ...
Luis Enrique Sucar
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Probabilistic Graphical Models of Dyslexia
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015Reading is a complex cognitive process, errors in which may assume diverse forms. In this study, introducing a novel approach, we use two families of probabilistic graphical models to analyze patterns of reading errors made by dyslexic people: an LDA-based model and two Naeve Bayes models which differ by their assumptions about the generation process ...
Yair Lakretz +3 more
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Survey of Probabilistic Graphical Models
2013 10th Web Information System and Application Conference, 2013Probabilistic graphical model (PGM) is a generic model that represents the probability-based relationships among random variables by a graph, and is a general method for knowledge representation and inference involving uncertainty. In recent years, PGM provides an important means for solving the uncertainty of intelligent information field, and becomes
Hongmei Li +3 more
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THE HUGIN TOOL FOR PROBABILISTIC GRAPHICAL MODELS
International Journal on Artificial Intelligence Tools, 2005As the framework of probabilistic graphical models becomes increasingly popular for knowledge representation and inference, the need for efficient tools for its support is increasing. The Hugin Tool is a general purpose tool for construction, maintenance, and deployment of Bayesian networks and influence diagrams.
Anders L. Madsen +3 more
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Probabilistic Graphical Models for Computational Biomedicine
Methods of Information in Medicine, 2003Summary Background: As genomics becomes increasingly relevant to medicine, medical informatics and bioinformatics are gradually converging into a larger field that we call computational biomedicine. Objectives: Developing a computational framework that is common to the different disciplines that compose computational biomedicine ...
Bart De Moor
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