_optimal-prediction-in-spatio-temporal-systems-nonparametric-methods-for-forecasting-pattern-discovery-and-dimension-redu.jpg "Optimal Prediction in Spatio-Temporal Systems Nonparametric Methods for Forecasting, Pattern Discovery, and Dimension Reduction from vary hard Video Screenshot Preview")
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⏲ Duration: 27 min 85 sec
✓ Published: 11-Nov-2012
✓ Published: 11-Nov-2012
Description:
Many important scientific and data-driven problems involve quantities which vary over both space and time. Examples include functional magnetic resonance imaging (fMRI), climate data, or experimental studies in physics and chemistry. Principal goals of many methods in statistics, machine learning, and signal processing are to use this data and i) extract informative structures and remove noisy, uninformative parts; ii) understand and reconstruct underlying spatio-temporal dynamics that govern th
Many important scientific and data-driven problems involve quantities which vary over both space and time. Examples include functional magnetic resonance imaging (fMRI), climate data, or experimental studies in physics and chemistry. Principal goals of many methods in statistics, machine learning, and signal processing are to use this data and i) extract informative structures and remove noisy, uninformative parts; ii) understand and reconstruct underlying spatio-temporal dynamics that govern th
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