Results 141 to 150 of about 522,455 (311)
Position: topological deep learning is the new frontier for relational learning
Topological deep learning (TDL) is a rapidly evolving field that uses topological features to understand and design deep learning models. This paper posits that TDL is the new frontier for relational learning.
Nasrin, F +21 more
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Global machine learning potentials for molecular crystals
The Journal of Chemical PhysicsMolecular crystals are difficult to model with accurate first-principles methods due to large unit cells. On the other hand, accurate modeling is required as polymorphs often differ by only 1 kJ/mol. Machine learning interatomic potentials promise to provide accuracy of the baseline first-principles methods with a cost lower by orders of magnitude ...
Ivan Žugec +2 more
openaire +4 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
Machine Learning Interatomic Potentials for Heterogeneous Catalysis
Chemistry – A European JournalAbstractAtomistic modeling can provide valuable insights into the design of novel heterogeneous catalysts as needed nowadays in the areas of, e. g., chemistry, materials science, and biology. Classical force fields and ab initio calculations have been widely adopted in molecular simulations.
Tang, Deqi +2 more
openaire +2 more sources
Design and analysis of quantum machine learning: a survey
Connection ScienceMachine learning has demonstrated tremendous potential in solving real-world problems. However, with the exponential growth of data amount and the increase of model complexity, the processing efficiency of machine learning declines rapidly.
Linshu Chen +6 more
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr +16 more
wiley +1 more source
Using Automated Machine Learning for Spatial Prediction—The Heshan Soil Subgroups Case Study
Recently, numerous spatial prediction methods with diverse characteristics have been developed. Selecting an appropriate spatial prediction method, along with its data preprocessing and parameter settings, presents a challenging task for many users ...
Cheng-Zhi Qin, Peng Liang, A-Xing Zhu
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Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Abstraction for Bayesian Reinforcement Learning in Factored POMDPs
Publisher Copyright: © 2025, Transactions on Machine Learning Research. All rights reserved.Bayesian reinforcement learning provides an elegant solution to addressing the explo-ration–exploitation trade-off in Partially Observable Markov Decision ...
Starre, Rolf A.N. +4 more
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Machine Learning Applications in Seismology
The purpose of this Special Issue is to immerse readers in the transformative impact of machine learning-based artificial intelligence on seismology. From digital seismic data processing to the development of structured seismic catalogs, AI technology is
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