Machine learning and physics merge to enhance liquid-gas phase transition predictions
Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that ...
Assembly Mag6d
Making Sense of Machine Data With Time Series Databases
A time series database management system (DBMS) efficiently handles large volumes of time-stamped data from sensors and ...
Lifan Wu, Applied Scientist at Amazon, Leads Pioneering Research in High-Dimensional Operations Research
Lifan Wu, an Applied Scientist at Amazon, specializes in high-dimensional data analysis and machine learning. Her research on regularly varying ...
GitHub8d
Machine Learning for .NET
ML.NET is a cross-platform open-source machine learning (ML) framework for .NET. ML.NET allows developers to easily build, train, deploy, and consume custom models in their .NET applications without ...
What is TensorFlow?
Developed by Google, TensorFlow is a software framework that’s widely used for training and inference of neural networks.
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SHREC: A Physics-Based Machine Learning Approach to Time Series Analysis
Reconstructing unmeasured causal drivers of complex time series from observed response data represents ... causal driver reconstruction usually rely on signal processing or machine learning frameworks ...