As part of the community reciprocation that furthers research in any field, authors who submit articles to JMLMC acknowledge that they may be asked to review other articles for the journal.

Enquiries can be directed to Editor-in-Chief Dongbin Xiu at xiu.16@osu.edu.

Objetivos y Alcance

The Journal of Machine Learning for Modeling and Computing (JMLMC) focuses on the study of machine learning methods for modeling and scientific computing. The scope of the journal includes, but is not limited to, research of the following types: (1) the use of machine learning techniques to model real-world problems such as physical systems, social sciences, biology, etc.; (2) the development of novel numerical strategies, in conjunction of machine learning methods, to facilitate practical computation; and (3) the fundamental mathematical and numerical analysis for understanding machine learning methods.

Artículos más Descargados

LIMITATIONS OF PHYSICS INFORMED MACHINE LEARNING FOR NONLINEAR TWO-PHASE TRANSPORT IN POROUS MEDIA
Olga Fuks, Hamdi A. Tchelepi

TENSOR BASIS GAUSSIAN PROCESS MODELS OF HYPERELASTIC MATERIALS
Ari L. Frankel, Reese E. Jones, Laura P. Swiler

MACHINE LEARNING FOR TRAJECTORIES OF PARAMETRIC NONLINEAR DYNAMICAL SYSTEMS
Roland Pulch, Maha Youssef

TRAINABILITY OF ReLU NETWORKS AND DATA-DEPENDENT INITIALIZATION
Yeonjong Shin, George Em Karniadakis

LEARNING REDUCED SYSTEMS VIA DEEP NEURAL NETWORKS WITH MEMORY
Xiaohan Fu, Lo-Bin Chang, Dongbin Xiu