A Logic for Checking the Probabilistic Steady-State Properties of Reaction Networks [PDF]
Journal of Computational Biology, 2017 Designing probabilistic reaction models and determining their stochastic kinetic parameters are major issues in systems biology. To assist in the construction of reaction network models, we introduce a logic that allows one to express asymptotic properties about the steady-state stochastic dynamics of a reaction network.
Vincent Picard +2 more
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Small Lung Nodules Detection Based on Fuzzy-Logic and Probabilistic Neural Network With Bioinspired Reinforcement Learning [PDF]
IEEE transactions on fuzzy systems, 2019 Internal organs, like lungs, are very often examined by the use of screening methods. For this purpose, we present an evaluation model based on a composition of fuzzy system combined with a neural network.
Giacomo Capizzi +4 more
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PRG4CNN: A Probabilistic Model Checking-Driven Robustness Guarantee Framework for CNNs [PDF]
EntropyAs an important kind of DNN (deep neural network), CNN (convolutional neural network) has made remarkable progress and been widely used in the vision and decision-making of autonomous robots.
Yang Liu, Aohui Fang
doaj +2 more sources
Differentiable Probabilistic Logic Networks
, 2019 Probabilistic logic reasoning is a central component of such cognitive architectures as OpenCog. However, as an integrative architecture, OpenCog facilitates cognitive synergy via hybridization of different inference methods. In this paper, we introduce a differentiable version of Probabilistic Logic networks, which rules operate over tensor truth ...
Alexey Potapov +3 more
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Probabilistic Logic Neural Networks for Reasoning
, 2019 Knowledge graph reasoning, which aims at predicting the missing facts through reasoning with the observed facts, is critical to many applications. Such a problem has been widely explored by traditional logic rule-based approaches and recent knowledge graph embedding methods.
Meng Qu, Jian Tang
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Probabilistic Logic Graph Attention Networks for Reasoning
Companion Proceedings of the Web Conference 2020, 2020 Knowledge base completion, which involves the prediction of missing relations between entities in a knowledge graph, has been an active area of research.
L. Vivek +3 more
semanticscholar +3 more sources
Quantum Logic Networks for Probabilistic and Controlled Teleportation of Unknown Quantum States [PDF]
Communications in Theoretical Physics, 2004 9 pages, 5 ...
Ting Gao
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Quantum logic network for probabilistic cloning the quantum states
, 2003 We construct efficient quantum logic network for probabilistic cloning the quantum states used in implemented tasks for which cloning provides some enhancement in performance.
Ting Gao, Fengli Yan, Zhi‐Xi Wang
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Efficient Probabilistic Logic Reasoning with Graph Neural Networks
, 2020 Markov Logic Networks (MLNs), which elegantly combine logic rules and probabilistic graphical models, can be used to address many knowledge graph problems. However, inference in MLN is computationally intensive, making the industrial-scale application of MLN very difficult.
Yuyu Zhang +6 more
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Development of breast cancer diagnosis system based on fuzzy logic and probabilistic neural network
Eastern-European Journal of Enterprise Technologies, 2020 Breast cancer is one of the most common kinds of cancers that infect females in the whole world. It has happened when the cells in breast tissues start to grow in an uncontrollable way.
Taha Mohammed Hasan +2 more
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