Many books on artificial intelligence (AI) illuminate the pathologies of AI. These pathologies are created by artificial ...

Abstract: This article presents 3DNN-Xplorer, the first machine learning (ML)-based framework for predicting the performance of heterogeneous 3-D deep neural network (DNN) accelerators. Our ML ...

Using Google Earth imagery and 2019-2022 Sentinel-2 datasets, Chinese scientists have developed a two-stage classification framework to obtain the annual global dataset of solar photovoltaic panels at ...

Abstract: This article introduces a machine learning (ML) framework for the design of space–time-coding digital metasurface elements (STCDMEs), commonly used in reconfigurable intelligent surface (RIS ...

Eric D. Boyd of responsiveX previews his VSLive! 2025 session at Microsoft HQ in August where he explains how Azure ML empowers teams to build, deploy, and manage machine learning models with ease and ...

APPFL, Advanced Privacy-Preserving Federated Learning, is an open-source and highly extensible software framework that allows research communities to implement, test ...

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...

Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou 350207, PR China Department of Chemical and Biomolecular ...

Machine learning frameworks can be intimidating. Their codebases are often massive and complex, making source code nearly impossible to read. Fortunately, there's the Readable ML Framework, which ...

In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes in the geometry of the physical settings of PDEs. Called DIMON, the new ...