Aims and Scope
Journal of Machine Learning (JML) publishes high quality research papers in all areas of machine learning, including innovative algorithms of machine learning, theories of machine learning, important applications of machine learning in AI, natural sciences, social sciences, and engineering etc. The journal emphasizes a balanced coverage of both theory and practice. The journal is published in a timely fashion in electronic form. All articles in JML are open-access and there is no charge for the authors.
Articles
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Neural Stochastic Volterra Equations: Learning Path-Dependent Dynamics
23793 129 Pages:264-289 -
A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions
23974 135 Pages:290-317
Journal information
Online Issn
2790-2048
Print Issn
2790-203X
Abstracted and indexed in
MathSciNet
zbMATH Open