Holdings Information

Bibliographic Record Display

• Uniform Title:APL machine learning (Online)
  
• Title:APL machine learning [electronic resource].
  
• ISSN:2770-9019
  
• Published/Created:[Melville, New York] : AIP Publishing, LLC, 2023-
  
• Links:Full text
  

• Yale Holdings

  Holdings Record Display

  • Location:Yale Internet Resource
    Information about Off Campus Access
    
    
  • Call Number: None
    
  • Status:No information available 
  • Notes: Online Resource
    

   
• Frequency:Quarterly
  
• Extent:Began with: Volume 1, Issue 1 (March 2023)
  
• Local Notes:Access is available to the Yale community.
  
• Notes:Volume 1, Issue 1 (March 2023); title from cover image (aps.scitation.org viewed Mar. 1, 2023).
  Volume 1, Issue 1 (March 2023) (aps.scitation.org viewed Mar. 1, 2023).
  
• Access and use:Access restricted by licensing agreement.
• Summary:Research for two communities: researchers who use machine learning (ML) and data-driven approaches for physical sciences and related disciplines, and researchers from these disciplines who work on novel concepts, including materials, devices, systems, and algorithms relevant for the development of better ML and AI technologies. The journal also considers research that substantially describes quantitative models and theories, especially if the research is validated with experimental results.
  
• Variant and related titles:APL mach. learn.
  APL machine learning
  APL mach. learn.
  AML
  
• Format:Periodical
• Subjects:Machine learning--Periodicals.
  Physical sciences--Periodicals.