Results 41 to 50 of about 224,550 (312)
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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eLife, 2022 The lateral prefrontal cortex (LPFC) of humans enables flexible goal-directed behavior. However, its functional organization remains actively debated after decades of research.
Majd Abdallah +3 more
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MATRIX-VECTOR ALGORITHMS OF LOCAL POSTERIORI INFERENCE IN ALGEBRAIC BAYESIAN NETWORKS ON QUANTA PROPOSITIONS [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2015 Posteriori inference is one of the three kinds of probabilistic-logic inferences in the probabilistic graphical models theory and the base for processing of knowledge patterns with probabilistic uncertainty using Bayesian networks. The paper deals with a
A. A. Zolotin +2 more
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Argumentation-Based Query Answering under Uncertainty with Application to Cybersecurity
Big Data and Cognitive Computing, 2022 Decision support tools are key components of intelligent sociotechnical systems, and their successful implementation faces a variety of challenges, including the multiplicity of information sources, heterogeneous format, and constant changes.
Mario A. Leiva +3 more
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A Unified Approach to Semantic Information and Communication Based on Probabilistic Logic
IEEE Access, 2022 Traditionally, studies on technical communication (TC) are based on stochastic modeling and manipulation. This is not sufficient for semantic communication (SC) where semantic elements are logically connected, rather than stochastically correlated.
Jinho Choi, Seng W. Loke, Jihong Park
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Probabilistic description logic programs [PDF]
International Journal of Approximate Reasoning, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Logical Rule-Based Knowledge Graph Reasoning: A Comprehensive Survey
Mathematics, 2023 With its powerful expressive capability and intuitive presentation, the knowledge graph has emerged as one of the primary forms of knowledge representation and management.
Zefan Zeng, Qing Cheng, Yuehang Si
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A History of Probabilistic Inductive Logic Programming
Frontiers in Robotics and AI, 2014 The field of Probabilistic Logic Programming (PLP) has seen significant advances in the last 20 years, with many proposals for languages that combine probability with logic programming.
Fabrizio eRiguzzi +2 more
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Safe Reinforcement Learning via Probabilistic Logic Shields [PDF]
International Workshop on Neural-Symbolic Learning and Reasoning, 2023 Safe Reinforcement learning (Safe RL) aims at learning optimal policies while staying safe. A popular solution to Safe RL is shielding, which uses a logical safety specification to prevent an RL agent from taking unsafe actions.
Wen-Chi Yang +3 more
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Symbolic Learning and Reasoning With Noisy Data for Probabilistic Anchoring
Frontiers in Robotics and AI, 2020 Robotic agents should be able to learn from sub-symbolic sensor data and, at the same time, be able to reason about objects and communicate with humans on a symbolic level.
Pedro Zuidberg Dos Martires +5 more
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