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Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation
Theory and Practice of Logic ProgrammingMany inductive logic programming (ILP) methods are incapable of learning programs from probabilistic background knowledge, for example, coming from sensory data or neural networks with probabilities.
Fieke Hillerström, G. Burghouts
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Logic‐based probabilistic network model to detect and track faults in a process system
Process safety progress, 2019Process systems are becoming complex due to a higher dependency among operational variables and complex control loops. Principal component analysis (PCA) is widely used to reduce the dimensionality of the complex process systems, while Bayesian networks (
Amr Ibrahim Tahoon +3 more
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Probabilistic Event Calculus Based on Markov Logic Networks [PDF]
, 2011 In this paper, we address the issue of uncertainty in event recognition by extending the Event Calculus with probabilistic reasoning. Markov Logic Networks are a natural candidate for our logic-based formalism. However, the temporal semantics of Event Calculus introduce a number of challenges for the proposed model.
Anastasios Skarlatidis +3 more
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A probabilistic logic neuron network for associative learning
, 1989 Wing‐Kay Kan, Igor Aleksander
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A stochastic logic neural network as a deterministic and probabilistic Hopfield network
IJCNN-91-Seattle International Joint Conference on Neural Networks, 2002Summary form only given. The information processing of a stochastic logic neural network, which is one of the pulse-coded artificial neural network families, was investigated. This network realizes pseudo-analog performance with some local learning rules by using a digital circuit, and therefore it suits silicon technology. The limited synaptic weights
Yasuji Sawada, Y. Kondo
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Set stability and synchronization of logical networks with probabilistic time delays
Journal of the Franklin Institute, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xueying Ding, Haitao Li, Shuling Wang
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PRO2SAT: Systematic Probabilistic Satisfiability logic in Discrete Hopfield Neural Network
Advances in Engineering Software, 2023Ju Chen +7 more
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Asymptotical stability of continuous-time probabilistic logic networks based on transition rate
Science China Information Sciences, 2023Zhitao Li, Yuqian Guo, W. Gui
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Probabilistic Modeling of Failure Dependencies Using Markov Logic Networks
2013 IEEE 19th Pacific Rim International Symposium on Dependable Computing, 2013We present a methodology for the probabilistic modeling of failure dependencies in large, complex systems using Markov Logic Networks (MLNs), a state-of-the-art probabilistic relational modeling technique in machine learning. We illustrate this modeling methodology on example system architectures, and show how the the Probabilistic Consistency Engine ...
Shalini Ghosh +3 more
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2024 5th International Conference on Smart Electronics and Communication (ICOSEC)
This research work proposes a secured privacy preservation scheme for wireless sensor networks (WSNs) that integrates multiple advanced techniques to ensure robust data confidentiality, integrity, and traceability.
S. Shifani +5 more
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This research work proposes a secured privacy preservation scheme for wireless sensor networks (WSNs) that integrates multiple advanced techniques to ensure robust data confidentiality, integrity, and traceability.
S. Shifani +5 more
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