Critical review on data-driven approaches for learning from accidents: comparative analysis and future research
Y Niu, Y Fan, X Ju - Safety science, 2024 - Elsevier
Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …
human society. Industrial accident prevention is also amid this change. Although many …
Exploring causal learning through graph neural networks: an in-depth review
In machine learning, exploring data correlations to predict outcomes is a fundamental task.
Recognizing causal relationships embedded within data is pivotal for a comprehensive …
Recognizing causal relationships embedded within data is pivotal for a comprehensive …
Balanced influence maximization in social networks based on deep reinforcement learning
Balanced influence maximization aims to balance the influence maximization of multiple
different entities in social networks and avoid the emergence of filter bubbles and echo …
different entities in social networks and avoid the emergence of filter bubbles and echo …
A meta-reinforcement learning algorithm for causal discovery
AWM Sauter, E Acar… - Conference on Causal …, 2023 - proceedings.mlr.press
Uncovering the underlying causal structure of a phenomenon, domain or environment is of
great scientific interest, not least because of the inferences that can be derived from such …
great scientific interest, not least because of the inferences that can be derived from such …
Active learning based on similarity level histogram and adaptive-scale sampling for very high resolution image classification
In remote sensing image classification, active learning aims to obtain an excellent
classification model by selecting informative or representative training samples. However …
classification model by selecting informative or representative training samples. However …
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
Causal discovery is the challenging task of inferring causal structure from data. Motivated by
Pearl's Causal Hierarchy (PCH), which tells us that passive observations alone are not …
Pearl's Causal Hierarchy (PCH), which tells us that passive observations alone are not …
A Survey on Deep Active Learning: Recent Advances and New Frontiers
Active learning seeks to achieve strong performance with fewer training samples. It does this
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
[HTML][HTML] Causal reasoning in Software Quality Assurance: A systematic review
Abstract Context: Software Quality Assurance (SQA) is a fundamental part of software
engineering to ensure stakeholders that software products work as expected after release in …
engineering to ensure stakeholders that software products work as expected after release in …
[HTML][HTML] Metaheuristics-guided active learning for optimizing reaction conditions of high-performance methane conversion
GS Na, HW Kim - Applied Soft Computing, 2024 - Elsevier
Converting greenhouse gases into value-added chemical compounds has been widely
studied in chemical science and engineering for sustainable industry. In particular …
studied in chemical science and engineering for sustainable industry. In particular …
Modeling the causal mechanism in process safety management (PSM) systems from historical accidents
Y Niu, Y Fan, X Ju, C Hao, X Yang - Journal of Loss Prevention in the …, 2024 - Elsevier
Process safety management (PSM) underpins reducing major accidents in the process
industries. For decades, PSM systems have been implemented globally. However, few …
industries. For decades, PSM systems have been implemented globally. However, few …