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What is inference graph in Tensorflow?

Membership function

Inference engine

Optimization problem

Adaptive neuro fuzzy inference system

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Proceedings Article•DOI Some Extensions of Membership Graphs for Picture Inference Systems Pham Van Viet, Hoang Thi Minh Chau, Le Hoang Son, Pham Van Hai - Show less +3 more 01 Oct 2015 16 Citations	The findings of the paper suggest the most efficient membership graph(s) that can be used in the picture inference system.
Open access•Journal Article•DOI Multiresolution Network Models Bailey K. Fosdick, Tyler H. McCormick, Thomas Brendan Murphy, Tin Lok James Ng, Ted Westling - Show less +4 more 01 Jan 2019-Journal of Computational and Graphical Statistics 18 Citations	We show that our model class is projective, highlighting an ongoing discussion in the social network modeling literature on the dependence of inference paradigms on the size of the observed graph.
Open access•Journal Article•DOI Learning Over Multitask Graphs—Part I: Stability Analysis Roula Nassif, Stefan Vlaski, Cedric Richard, Ali H. Sayed - Show less +3 more 21 Apr 2020 22 Citations	The smoothness condition softens the transition in the tasks among adjacent nodes and allows incorporating information about the graph structure into the solution of the inference problem.
Proceedings Article•DOI Distributed Inference Over Multitask Graphs Under Smoothness Roula Nassif, Stefan Vlaski, Ali H. Sayed - Show less +2 more 23 Jun 2018 11 Citations	The smoothness requirement softens the transition in the tasks among adjacent nodes and allows incorporating information about the graph structure into the solution of the inference problem.
Open access•Book Chapter•DOI Conditioning graphs: practical structures for inference in bayesian networks Kevin Grant, Michael C. Horsch - Show less +1 more 05 Dec 2005 7 Citations	The inference engine is sufficiently simple as to avoid space-limitation and be easily implemented in almost any environment.
Open access•Proceedings Article•DOI Inference in Probabilistic Graphical Models by Graph Neural Networks KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow - Show less +7 more 01 Nov 2019 54 Citations	We first show that the architecture of GNNs is well-matched to inference tasks.

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In Linguistic, what is an inference?2 answersIn linguistics, an inference refers to the process of deriving meaning or information that is not explicitly stated in a given utterance or text. It involves making logical connections and drawing conclusions based on contextual cues and background knowledge. Inferences play a crucial role in understanding language and can involve various types such as implicatures, presuppositions, supplements, and homogeneity. They are not specific to language and can also be observed in nonlinguistic information, suggesting a deeper cognitive source for the inferential typology. In the field of grammatical inference, it refers to the process of learning grammars and languages from data, which finds applications in syntactic pattern recognition and natural language acquisition. Inferences are made by listeners and readers to comprehend oral and written discourse, and they contribute to the overall understanding of a text.

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