A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
D'ya like dags? a survey on structure learning and causal discovery
Causal reasoning is a crucial part of science and human intelligence. In order to discover
causal relationships from data, we need structure discovery methods. We provide a review …
causal relationships from data, we need structure discovery methods. We provide a review …
[HTML][HTML] Condition monitoring using machine learning: A review of theory, applications, and recent advances
In modern industry, the quality of maintenance directly influences equipment's operational
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
uptime and efficiency. Hence, based on monitoring the condition of the machinery, predictive …
A machine learning based approach for predicting blockchain adoption in supply Chain
The purpose of this paper is to provide a decision support system for managers to predict an
organization's probability of successful blockchain adoption using a machine learning …
organization's probability of successful blockchain adoption using a machine learning …
Survey and evaluation of causal discovery methods for time series
CK Assaad, E Devijver, E Gaussier - Journal of Artificial Intelligence …, 2022 - jair.org
We introduce in this survey the major concepts, models, and algorithms proposed so far to
infer causal relations from observational time series, a task usually referred to as causal …
infer causal relations from observational time series, a task usually referred to as causal …
Concepts of artificial intelligence for computer-assisted drug discovery
X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …
opportunities for the discovery and development of innovative drugs. Various machine …
Black-box vs. white-box: Understanding their advantages and weaknesses from a practical point of view
O Loyola-Gonzalez - IEEE access, 2019 - ieeexplore.ieee.org
Nowadays, in the international scientific community of machine learning, there exists an
enormous discussion about the use of black-box models or explainable models; especially …
enormous discussion about the use of black-box models or explainable models; especially …
Knowledge graph completion: A review
Z Chen, Y Wang, B Zhao, J Cheng, X Zhao… - Ieee …, 2020 - ieeexplore.ieee.org
Knowledge graph completion (KGC) is a hot topic in knowledge graph construction and
related applications, which aims to complete the structure of knowledge graph by predicting …
related applications, which aims to complete the structure of knowledge graph by predicting …
Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems
Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …
training data. A potential solution is the additional integration of prior knowledge into the …
Bayesian structure learning with generative flow networks
In Bayesian structure learning, we are interested in inferring a distribution over the directed
acyclic graph (DAG) structure of Bayesian networks, from data. Defining such a distribution …
acyclic graph (DAG) structure of Bayesian networks, from data. Defining such a distribution …