Results 61 to 70 of about 1,042,976 (291)
Probabilistic Logic Models for the Lightning Network
Cryptography, 2022 The Lightning Network (LN) has emerged as one of the prominent solutions to overcome the biggest limit of blockchain based on PoW: scalability. LN allows for creating a layer on top of an existing blockchain where users can send payments and micro ...
Damiano Azzolini, Fabrizio Riguzzi
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Artificial molecular machines and motors—Design and control of nanoscale motion
FEBS Letters, EarlyView.Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley +1 more source
Self-Organized Complexity and Coherent Infomax from the Viewpoint of Jaynes’s Probability Theory
Information, 2012 This paper discusses concepts of self-organized complexity and the theory of Coherent Infomax in the light of Jaynes’s probability theory. Coherent Infomax, shows, in principle, how adaptively self-organized complexity can be preserved and improved by ...
William A. Phillips
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Probabilistic Similarity Logic
CoRR, 2012 Many machine learning applications require the ability to learn from and reason about noisy multi-relational data. To address this, several effective representations have been developed that provide both a language for expressing the structural regularities of a domain, and principled support for probabilistic inference.
Matthias Bröcheler +2 more
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Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
SICE Journal of Control, Measurement, and System Integration, 2023 Our study introduces a novel approach that combined probabilistic logic and multimodal spatial concepts to enable a robot to efficiently acquire place–object relationships in a new home environment with few learning iterations.
Shoichi Hasegawa +4 more
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Probabilistic Description Logics [PDF]
, 1994 Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)
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Logic and Probabilistic Update [PDF]
, 2014 This chapter surveys recent work on probabilistic extensions of epistemic and dynamic-epistemic logics (the latter include the basic system of public announcement logic as well as the full product update logic). It emphasizes the importance of higher-order information as a distinguishing feature of these logics.
Demey, Lorenz, Kooi, Barteld
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Probabilistic inductive constraint logic [PDF]
Machine Learning, 2020 AbstractProbabilistic logical models deal effectively with uncertain relations and entities typical of many real world domains. In the field of probabilistic logic programming usually the aim is to learn these kinds of models to predict specific atoms or predicates of the domain, called target atoms/predicates. However, it might also be useful to learn
Fabrizio Riguzzi +4 more
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Probabilistic logic under uncertainty [PDF]
, 2007 Probabilistic logic combines the capability of binary logic to express the structure of argument models with the capacity of probabilities to express degrees of truth of those arguments.
Josang, Audun
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