High-efficient ab initio Bayesian active learning method and applications in prediction of two-dimensional functional materials.
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DOI: 10.1039/d1nr03886a
Abstract: Beyond the conventional trial-and-error method, machine learning offers a great opportunity to accelerate the discovery of functional materials, but still often suffers from difficulties such as limited materials data and the unbalanced distribution of target… read more here.
Keywords: initio bayesian; learning method; functional materials; active learning ... See more keywords
DeepWE: A Deep Bayesian Active Learning Waypoint Estimator for Indoor Walkers
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2023.3234600
Abstract: Waypoint estimation (WE) has a wide range of applications for indoor walkers, such as fire rescue and navigation to find exit doors, lifts, or stairs as examples of waypoints, etc. Data-driven WE has been on… read more here.
Keywords: waypoint; bayesian active; learning waypoint; active learning ... See more keywords
Bayesian Active Meta-Learning for Reliable and Efficient AI-Based Demodulation
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DOI: 10.1109/tsp.2022.3220035
Abstract: Two of the main principles underlying the life cycle of an artificial intelligence (AI) module in communication networks are adaptation and monitoring. Adaptation refers to the need to adjust the operation of an AI module… read more here.
Keywords: meta learning; bayesian active; active meta; meta ... See more keywords
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning
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DOI: 10.48550/arxiv.2205.15458
Abstract: Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling… read more here.
Keywords: bayesian active; active learning; spectroscopy; scanning probe ... See more keywords