Predicting Hurricane Trajectories ResearchInsightsCommentarysiam.org FeedsData ScienceGeosciences and Math of Planet Earth Statistical modeling and machine learning methods vary in their effectiveness at predicting hurricane trajectories.
Drift Matters: Unsupervised Anomaly Detection and National Security ResearchInsightsCommentarysiam.org FeedsData ScienceGeosciences and Math of Planet Earth Few existing algorithms can handle the concept drift challenges that are specific to maritime trajectories.
Deep Learning for Digital Pathology: Detecting Skin Diseases with Normalizing Flows ResearchInsightsCommentarysiam.org FeedsComputational Science & Numerical AnalysisData ScienceImaging ScienceLife Sciences Deep learning can assist in the diagnosis of skin diseases by defining changes in the skin as out-of-distribution samples.
Learning Oscillatory Navier-Stokes Flows and Causal Linear Operators with Deep Neural Network Algorithms ResearchInsightsCommentarysiam.org FeedsComputational Science & Numerical AnalysisData ScienceLinear AlgebraAnalysis and Partial Differential Equations Neural networks address nonlinear problems with highly oscillatory solutions and approximate operators of causal physical systems.
Speeding Up Solar Wind Forecasts with Reduced-order Modeling ResearchInsightsCommentarysiam.org FeedsComputational Science & Numerical AnalysisData ScienceDynamical Systems, Nonlinear WavesGeosciences and Math of Planet EarthUncertainty Quantification Shifted operator inference is a data-driven, projection-based, reduced-order model that predicts the solar wind near Earth.