Learning concise and descriptive attributes for visual recognition

A Yan, Y Wang, Y Zhong, C Dong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Recent advances in foundation models present new opportunities for interpretable visual
recognition--one can first query Large Language Models (LLMs) to obtain a set of attributes …

Designing a feature selection method based on explainable artificial intelligence

J Zacharias, M von Zahn, J Chen, O Hinz - Electronic Markets, 2022 - Springer
Nowadays, artificial intelligence (AI) systems make predictions in numerous high stakes
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …

[HTML][HTML] Flood susceptibility assessment in urban areas via deep neural network approach

T Panfilova, V Kukartsev, V Tynchenko, Y Tynchenko… - Sustainability, 2024 - mdpi.com
Floods, caused by intense rainfall or typhoons, overwhelming urban drainage systems, pose
significant threats to urban areas, leading to substantial economic losses and endangering …

An interpretable AI model for recurrence prediction after surgery in gastrointestinal stromal tumour: an observational cohort study

D Bertsimas, GA Margonis, S Tang, A Koulouras… - …, 2023 - thelancet.com
Background There are several models that predict the risk of recurrence following resection
of localised, primary gastrointestinal stromal tumour (GIST). However, assessment of …

Spatiotemporal Patterns of Methane and Nitrous Oxide Emissions in China's Inland Waters Identified by Machine Learning Technique

C Yang, WJ Du, RL He, YR Hu, H Liu, T Huang… - ACS ES&T …, 2023 - ACS Publications
The fugitive emissions of greenhouse gases, primarily methane (CH4) and nitrous oxide
(N2O), from water environments have aroused global concern. However, there are currently …

Explainable AI: to reveal the logic of black-box models

Chinu, U Bansal - New Generation Computing, 2024 - Springer
Artificial intelligence (AI) is continuously evolving; however, in the last 10 years, it has gotten
considerably more difficult to explain AI models. With the help of explanations, end users …

Machine learning predictions of onset and oxidation potentials for methanol and ethanol electrooxidation: Comprehensive analysis and experimental validation

TW von Zuben, AG Salles Jr, JA Bonacin, SB Junior - Electrochimica Acta, 2025 - Elsevier
The onset and oxidation potentials of electrochemical reactions are pivotal in assessing
catalytic energy efficiency, spanning applications across various domains, including …

Outlier Summarization via Human Interpretable Rules

Y Deng, Y Wang, L Cao, L Qiao, Y Wang, J Xu… - Proceedings of the …, 2024 - dl.acm.org
Outlier detection is crucial for preventing financial fraud, network intrusions, and device
failures. Users often expect systems to automatically summarize and interpret outlier …

Advances in Feature Extraction for Brain Cancer Analysis: A Review of Traditional, Machine Learning, and Deep Learning Approaches

B Almuhaya, B Saha, MA Bazel - 2024 ASU International …, 2024 - ieeexplore.ieee.org
Brain cancer remains a formidable health challenge, necessitating continuous advancement
in diagnostic and therapeutic strategies. Feature extraction techniques, encompassing …

[HTML][HTML] Extracting tactics learned from self-play in general games

DJNJ Soemers, S Samothrakis, É Piette… - Information …, 2023 - Elsevier
Local, spatial state-action features can be used to effectively train linear policies from self-
play in a wide variety of board games. Such policies can play games directly, or be used to …