Search results for "inference"
showing 8 items of 478 documents
Causality-Aware Convolutional Neural Networks for Advanced Image Classification and Generation
2023
Smart manufacturing uses emerging deep learning models, and particularly Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), for different industrial diagnostics tasks, e.g., classification, detection, recognition, prediction, synthetic data generation, security, etc., on the basis of image data. In spite of being efficient for these objectives, the majority of current deep learning models lack interpretability and explainability. They can discover features hidden within input data together with their mutual co-occurrence. However, they are weak at discovering and making explicit hidden causalities between the features, which could be the reason behind the parti…
Explainable Fuzzy AI Challenge 2022 : Winner’s Approach to a Computationally Efficient and Explainable Solution
2022
An explainable artificial intelligence (XAI) agent is an autonomous agent that uses a fundamental XAI model at its core to perceive its environment and suggests actions to be performed. One of the significant challenges for these XAI agents is performing their operation efficiently, which is governed by the underlying inference and optimization system. Along similar lines, an Explainable Fuzzy AI Challenge (XFC 2022) competition was launched, whose principal objective was to develop a fully autonomous and optimized XAI algorithm that could play the Python arcade game “Asteroid Smasher”. This research first investigates inference models to implement an efficient (XAI) agent using rule-based …
Religious Diaspora: A New Approach to Its Existence and Meaning
2021
The present study aims to contribute to the discussion regarding the possibility of conceptualizing a religious diaspora. It proposes a new way of defining it, namely in relation to religious and not to ethno-territorial realities, but without editing the territorial dimension out. After sketching the definition on this theoretical basis, the study refers to six case studies, pointing to the way in which the definitory traits of a religious diaspora are actualized in each situation under study. The evaluation unravels the strengths of the concept as well as certain aspects that still need to be addressed in further research. The inference is that the capacity of religion to generate diaspor…
Continuum: A spatiotemporal data model to represent and qualify filiation relationships
2013
International audience; This work introduces an ontology-based spatio-temporal data model to represent entities evolving in space and time. A dynamic phenomenon generates a complex relationship network between the entities involved in the process. At the abstract level, the relationships can be identity or topological filiations. The existence of an identity filiation depends on whether the object changes its identity or not. On the other hand, topological filiations are based exclusively on the spatial component, like in the case of growth, reduction, merging or splitting. When combining identity and topological filiations, six filiation relationships are obtained, forming a second abstrac…
The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach
2021
Traditionally, intimate-partner violence has been considered a special type of crime that occurs behind closed doors, with different characteristics from street-level crime. The aim of this study is to analyze the spatial overlap of police calls reporting street-level and behind-closed-doors crime. We analyzed geocoded police calls in the 552 census-block groups of the city of Valencia, Spain, related to street-level crime (N = 26,624) and to intimate-partner violence against women (N = 11,673). A Bayesian joint model was run to analyze the spatial overlap. In addition, two Bayesian hierarchical models controlled for different neighborhood characteristics to analyze the relative risks. Resu…
‘Seeing the Dark’: Grounding Phenomenal Transparency and Opacity in Precision Estimation for Active Inference
2018
One of the central claims of the Self-model Theory of Subjectivity is that the experience of being someone - even in a minimal form - arises through a transparent phenomenal self-model, which itself can in principle be reduced to brain processes. Here, we consider whether it is possible to distinguish between phenomenally transparent and opaque states in terms of active inference. We propose a relationship of phenomenal opacity to expected uncertainty or precision; i.e., the capacity for introspective attention and implicit mental action. Thus we associate introspective attention with the deployment of 'precision' that may render the perceptual evidence (for action) opaque, while treating t…
Ordered fuzzy rules generation based on incremental dataset
2021
This paper proposes a novel approach for building transparent knowledge-based systems by generating interpretable fuzzy rules that allow for present dependences between quantitative variables by accounting for uncertainty and the dynamics of their values. In the approach, IF-THEN rules are used to show the conditional relationship between the ordered fuzzy numbers, which contain additional information about the tendencies of variables' value changes. This paper elaborates an approach of mining ordered fuzzy rules from numerical data included in an incremental database. This approach develops the ability to record uncertainty and its change in the context of rapidly changing data. In additio…
Prediction of the next value of a function
1981
The following model of inductive inference is considered. Arbitrary set tau = {tau_1, tau_2, ..., tau_n} of n total functions N->N is fixed. A "black box" outputs the values f(0), f(1), ..., f(m), ... of some function f from the set tau. Processing these values by some algorithm (a strategy) we try to predict f(m+1) from f(0), f(1), ..., f(m). Upper and lower bounds for average error numbers are obtained for prediction by using deterministic and probabilistic strategies.