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Neel Somani on formal methods and the future of machine learning safety

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...
Frontiers

Machine Learning for Inverse Design and Optimization of Metamaterials

In the domain of metamaterials, the push toward automated design has been accelerated by advances in generative machine learning. The advent of deep ...
IEEE

Spatial Modeling with Automated Machine Learning and Gaussian Process Regression Techniques for Imputing Wafer Acceptance Test Data

Abstract: The Wafer Acceptance Test (WAT) is a significant quality control measurement in the semiconductor industry. However, because the WAT process can be time-consuming and expensive, sampling ...
IEEE

Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions

Abstract: Machine learning has been integrated into numerous applications and has emerged as one of the most transformative technologies in our daily lives. In recent years, the number of individuals ...
The Conversation

The ‘one chatbot per child’ model for AI in classrooms conflicts with what research shows: Learning is a social process

Niral Shah does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
CNX Software

Edgi-Talk machine learning development kit features Infineon PSOC Edge E84 Edge AI SoC (Crowdfunding)

Edgi-Talk is a machine learning platform/development kit powered by an Infineon PSOC Edge E84 Arm Cortex-M55/M33 SoC featuring Arm Helium, an Arm Ethos-U55 micro NPU, and an ultra-low-power NNLite ...
Frontiers

Development of a machine learning-based predictive model for osteoporosis risk and its application in clinical decision support

1 Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China 2 Affiliated Hospital of Jiangxi University of Chinese Medicine, Nanchang, Jiangxi, China Objective: This study was aimed at ...
Journal of Medical Internet Research

Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model: Development, Multiregional Validation, and Clinical ...

Objective: This study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...