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cs.LG2025
Uncertainty quantification of neural network models of evolving processes via Langevin sampling
Cosmin Safta, Reese E. Jones, Ravi G. Patel +4
We propose a scalable, approximate inference hypernetwork framework for a general model of history-dependent processes. The flexible data model is based on a neural ordinary differ…
cs.LG2024★ 1 cited
Unsupervised Multimodal Fusion of In-process Sensor Data for Advanced Manufacturing Process Monitoring
Matthew McKinney, Anthony Garland, Dale Cillessen +5
Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments generate vast amounts of mu…