Results 91 to 100 of about 66,762 (195)
Interpretable machine learning for precision cognitive aging
Frontiers in Computational NeuroscienceIntroductionMachine performance has surpassed human capabilities in various tasks, yet the opacity of complex models limits their adoption in critical fields such as healthcare.
Abdoul Jalil Djiberou Mahamadou +6 more
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Interpretable Machine Learning for the Physical Sciences
, 2023 Would Kepler have discovered his laws if machine learning had been around in 1609? Or would he have been satisfied with the accuracy of some black box regression model, leaving Newton without the inspiration to find the law of gravitation? In this thesis
Cranmer, Miles Donald
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Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic
LifeBy applying AI techniques to a variety of pandemic-relevant data, artificial intelligence (AI) has substantially supported the control of the spread of the SARS-CoV-2 virus.
Hamed Khalili, Maria A. Wimmer
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Interpretable Machine Learning in Physics: A Review
CoRRMachine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulations. As artificial intelligence (AI) continues to grow in capability, these algorithms will enable many scientific discoveries beyond human capabilities.
Sebastian Johann Wetzel +4 more
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Interpretability by Design: New Interpretable Machine Learning Models and Methods
, 2020 As machine learning models are playing increasingly important roles in many real-life scenarios, interpretability has become a key issue for whether we can trust the predictions made by these models, especially when we are making some high-stakes ...
Chen, Chaofan
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Interpretable Machine Learning: A Case Study on Predicting Fuel Consumption in VLGC Ship Propulsion
Journal of Marine Science and EngineeringThe integration of machine learning (ML) in marine engineering has been increasingly subjected to stringent regulatory scrutiny. While environmental regulations aim to reduce harmful emissions and energy consumption, there is also a growing demand for ...
Aleksandar Vorkapić +2 more
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Kernel learning assisted synthesis condition exploration for ternary spinel
Communications MaterialsMachine learning and high-throughput experimentation have greatly accelerated the discovery of mixed metal oxide catalysts by leveraging their compositional flexibility.
Yutong Liu +3 more
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Probabilistic scoring lists for interpretable machine learning
Machine LearningAbstract A scoring system is a simple decision model that checks a set of features, adds a certain number of points to a total score for each feature that is satisfied, and finally makes a decision by comparing the total score to a threshold.
Jonas Hanselle +3 more
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XRGuard: A Model-Agnostic Approach to Ransomware Detection Using Dynamic Analysis and Explainable AI
IEEE AccessRansomware remains a persistent and evolving cybersecurity threat, demanding advanced and adaptable detection strategies. Traditional methods often fall short as signature-based systems are easily circumvented by emerging ransomware variants, while ...
M. Adnan Alvi, Zunera Jalil
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ON THE DEFINITION AND IMPORTANCE OF INTERPRETABILITY IN SCIENTIFIC MACHINE LEARNING
Journal of Machine Learning for Modeling and ComputingThough neural networks trained on large datasets have been successfully used to describe and predict many physical phenomena, there is a sense among scientists that, unlike traditional scientific models comprising simple mathematical expressions, their findings cannot be integrated into the body of scientific knowledge.
Conor Rowan, Alireza Doostan
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