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02/15/2022
An Extension Of Combinatorial Contextuality For Cognitive Protocols
This article extends the combinatorial approach to support the determina...
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03/21/2021
Structural block driven - enhanced convolutional neural representation for relation extraction
In this paper, we propose a novel lightweight relation extraction approa...
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03/07/2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
There has been a growing interest in model-agnostic methods that can mak...
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07/21/2020
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models
The use of sophisticated machine learning models for critical decision m...
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07/15/2020
Kernel Method based on Non-Linear Coherent State
In this paper, by mapping datasets to a set of non-linear coherent state...
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06/02/2020
Construction of 'Support Vector' Machine Feature Spaces via Deformed Weyl-Heisenberg Algebra
This paper uses deformed coherent states, based on a deformed Weyl-Heise...
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05/30/2020
QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision
This paper provides the foundations of a unified cognitive decision-maki...
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04/04/2020
Bistable Probabilities: A Unified Framework for Studying Rationality and Irrationality in Classical and Quantum Games
This article presents a unified probabilistic framework that allows both...
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02/21/2020
An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics
This paper explores interpretability techniques for two of the most succ...
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01/20/2020
Quantum-like Structure in Multidimensional Relevance Judgements
A large number of studies in cognitive science have revealed that probab...
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07/25/2019
Modelling Dynamic Interactions between Relevance Dimensions
Relevance is an underlying concept in the field of Information Science a...
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05/11/2019