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Long Term Time Series Forecasting

Oct 25, 2021
37:45
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1
Introduction
00:00 • 3min
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2
Is Quasi Periodic Really Periodic?
02:33 • 5min
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3
Is There a Parallel to Support Vector Machines?
07:52 • 4min
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4
The Copman Framework for Noise Robustness
11:29 • 3min
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5
Data in a I - The Platform for Everyday a I
14:41 • 5min
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6
Using Copman Theory in Machine Learning?
19:35 • 3min
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7
How to Predict the Demand of Energy in the New England Power Grid?
22:29 • 2min
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8
Is There Any Way to Inspect the Predictions?
24:30 • 5min
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9
Predicting the Moisture of Soil
29:48 • 3min
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10
The Non Linear Oscillation of the Brain
32:38 • 2min
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11
Applications in the Sciences?
34:47 • 3min
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Alex Mallen, Computer Science student at the University of Washington, and Henning Lange, a Postdoctoral Scholar in Applied Math at the University of Washington, join us today to share their work "Deep Probabilistic Koopman: Long-term Time-Series Forecasting Under Periodic Uncertainties."

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