Research data supporting "Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials".

Reproducibility archive for validation-first machine learning interatomic potentials for local lithium energetics in graphene-based battery motifs.

Yuhan Sun, Xiao Huang

A Scalable Distributed and Fault-Tolerant Architecture for Cloud-Based Machine Learning and Data Analysis

Grace Dooshima GBOR, Emmanuel Ogala, Donald Douglas Atsa’am, Iorshashe Agaji

Abstract The rapid growth of data-intensive applications has necessitated the development of scalable and efficient architectures for cloud-based machine learning and data analysis. This study proposes a scalable, distributed, and fault-tolerant architecture designed to address t…Read more

Before the Model: Why Datasets and Data Representation Define What Machine Learning Can Learn

Jean Franck Loa Rojas

Machine learning systems do not learn reality directly; they learn from the representations preserved in their datasets. This structured narrative review examines how dataset purpose, coverage, integrity, labeling, independence, reproducibility, governance, and continuity determi…Read more

Chemistry-stratified reliability audit of selective abstention for universal machine-learning interatomic potentials

Zeyu Fu

Version 0.3.0 provides the sanitized, hermetic code and frozen result records supporting the chemistry-stratified selective-abstention analysis. It includes the 32-UIP roster analysis, prototype-blocked confidence intervals, mechanism and sensitivity controls, manuscript sources,…Read more

A High-Performance Scalable Architecture for Cloud-Based Deep Learning and Data-Intensive Applications

Grace Dooshima GBOR, Emmanuel Ogala, Donald Douglas Atsa’am, Iorshashe Agaji

Abstract The rapid growth of big data and the increasing complexity of deep learning applications have created significant challenges for traditional data processing infrastructures, particularly in terms of scalability, performance, and resource efficiency. This study presents a…Read more

Village-Level Suitability Assessment For Litchi Cultivation In The Malwa Region Using Explainable Machine Learning And Geospatial Data

Dr. Pankaj Malik, Mishthi Patodia, Vedant soni, Deepika Kumari, Pragati Agrawal, Jaiswal Tanmay

Litchi is a high-value fruit crop traditionally cultivated in regions with favorable climatic and soil conditions. Expanding litchi cultivation into non-traditional areas such as the Malwa region of Madhya Pradesh requires accurate identification of suitable locations to minimize…Read more