A functional contextual account of background knowledge in categorization: Implications for artificial general intelligence and cognitive accounts of general knowledge
DJ Edwards, C McEnteggart… - Frontiers in …, 2022 - frontiersin.org
Psychology has benefited from an enormous wealth of knowledge about processes of
cognition in relation to how the brain organizes information. Within the categorization …
cognition in relation to how the brain organizes information. Within the categorization …
[HTML][HTML] Extracting knowledge from deep neural networks through graph analysis
The popularity of deep learning has increased tremendously in recent years due to its ability
to efficiently solve complex tasks in challenging areas such as computer vision and …
to efficiently solve complex tasks in challenging areas such as computer vision and …
Post-hoc Explanation Options for XAI in Deep Learning: The Insight Centre for Data Analytics Perspective
This paper profiles the recent research work on eXplainable AI (XAI), at the Insight Centre for
Data Analytics. This work concentrates on post-hoc explanation-by-example solutions to XAI …
Data Analytics. This work concentrates on post-hoc explanation-by-example solutions to XAI …
Towards neural network interpretability using commonsense knowledge graphs
Convolutional neural networks (CNNs) classify images by learning intermediate
representations of the input throughout many layers. In recent work, latent representations of …
representations of the input throughout many layers. In recent work, latent representations of …
Generating Local Textual Explanations for CNNs: A Semantic Approach Based on Knowledge Graphs
Abstract Explainable Artificial Intelligence (XAI) has recently become an active research field
due to the need for transparency and accountability when deploying AI models for high …
due to the need for transparency and accountability when deploying AI models for high …
Explaining cnns using knowledge extraction and graph analysis
Abstract Explainable Artificial Intelligence (XAI) has recently become an active research field
due to the need for transparency and accountability when deploying AI models for high …
due to the need for transparency and accountability when deploying AI models for high …
Explaining deep neural networks through knowledge extraction and graph analysis
VAC Horta - 2023 - doras.dcu.ie
Explainable Artificial Intelligence (XAI) has recently become an active research field due to
the need for transparency and accountability when deploying AI models for high-stake …
the need for transparency and accountability when deploying AI models for high-stake …
Knowledge Extraction from Auto-Encoders on Anomaly Detection Tasks Using Co-activation Graphs
D Selani, I Tiddi - Proceedings of the 11th Knowledge Capture …, 2021 - dl.acm.org
Deep neural networks have exploded in popularity and different types of networks are used
to solve a multitude of complex tasks. One such task is anomaly detection, that a type of …
to solve a multitude of complex tasks. One such task is anomaly detection, that a type of …