ML.NET is a cross-platform open-source machine learning (ML) framework for .NET ... With ML.NET, you can train models for a variety of scenarios, like classification, forecasting, and anomaly ...

Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada School of Biomedical Engineering, McMaster University, 1280 Main Street West, L8S 4L8 ...

supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.

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 ...

To address these challenges, we propose a mixed CNN-transformer network for Mars HSI classification with graph contrastive learning to enhance classification performance. Specifically, we introduce an ...

Department of Chemistry, University of Waterloo, 200 University Avenue W., Waterloo, Ontario N2L 3G1, Canada Waterloo Institute for Nanotechnology, University of Waterloo, 200 University Avenue W., ...

Abstract: Flow regime classification is essential for analyzing and modeling two-phase flows, as it demarcates the flow behavior and influences the selection of appropriate predictive models. Machine ...