Results 31 to 40 of about 258,177 (241)
Approximate Inference for Neural Probabilistic Logic Programming
International Conference on Principles of Knowledge Representation and Reasoning, 2021 DeepProbLog is a neural-symbolic framework that integrates probabilistic logic programming and neural networks. It is realized by providing an interface between the probabilistic logic and the neural networks.
Robin Manhaeve, G. Marra, L. D. Raedt
semanticscholar +1 more source
Ergodic sets as cell phenotype of budding yeast cell cycle. [PDF]
PLoS ONE, 2012 It has been suggested that irreducible sets of states in Probabilistic Boolean Networks correspond to cellular phenotype. In this study, we identify such sets of states for each phase of the budding yeast cell cycle.
Robert G Todd, Tomáš Helikar
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Self-supervised self-supervision by combining deep learning and probabilistic logic [PDF]
AAAI Conference on Artificial Intelligence, 2020 Labeling training examples at scale is a perennial challenge in machine learning. Self-supervision methods compensate for the lack of direct supervision by leveraging prior knowledge to automatically generate noisy labeled examples.
Hunter Lang, Hoifung Poon
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SoftwareX, 2022 The application of deep learning models to increasingly complex contexts has led to a rise in the complexity of the models themselves. Due to this, there is an increase in the number of hyper-parameters (HPs) to be set and Hyper-Parameter Optimization ...
Michele Fraccaroli +2 more
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PLoS ONE, 2021 A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze ...
Eric Garcia +8 more
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On the Coherence of Probabilistic Relational Formalisms
Entropy, 2018 There are several formalisms that enhance Bayesian networks by including relations amongst individuals as modeling primitives. For instance, Probabilistic Relational Models (PRMs) use diagrams and relational databases to represent repetitive Bayesian ...
Glauber De Bona, Fabio G. Cozman
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Sequential circuit design in quantum-dot cellular automata [PDF]
, 2008 In this work we present a novel probabilistic modeling scheme for sequential circuit design in quantum-dot cellular automata(QCA) technology. Clocked QCA circuits possess an inherent direction for flow of information which can be effectively modeled ...
Bhanja, S. +2 more
core +1 more source
Complexity, 2020 The goal of this research is to design an Artificial Intelligence controller for the active suspension system of vehicles. The Ring Probabilistic Logic Neural Network (RPLNN) architecture has been adopted to design the proposed controller, and the ...
Aydin Azizi
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Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models [PDF]
, 2005 Logical Bayesian Networks (LBNs) have recently been introduced as another language for knowledge based model construction of Bayesian networks, besides existing languages such as Probabilistic Relational Models (PRMs) and Bayesian Logic Programs (BLPs).
Fierens, Daan +3 more
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Link and Node Prediction in Metabolic Networks with Probabilistic Logic [PDF]
, 2012 Information on metabolic processes for hundreds of organisms is available in public databases. However, this information is often incomplete or affected by uncertainty. Systems capable to perform automatic curation of these databases and capable to suggest pathway-holes fillings are therefore needed.
Kimmig, Angelika, Costa, Fabrizio
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