Data Skeptic

Long Term Time Series Forecasting

Oct 25, 2021

37:45

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Highlights

AI Chapters

Episode notes

Is There a Parallel to Support Vector Machines?

03:37

The Copman Framework for Noise Robustness

03:12

Using Copman Theory in Machine Learning?

02:54

Introduction

3min

Is Quasi Periodic Really Periodic?

5min

Is There a Parallel to Support Vector Machines?

4min

The Copman Framework for Noise Robustness

3min

Data in a I - The Platform for Everyday a I

5min

Using Copman Theory in Machine Learning?

3min

How to Predict the Demand of Energy in the New England Power Grid?

2min

Is There Any Way to Inspect the Predictions?

5min

Predicting the Moisture of Soil

3min

10.

The Non Linear Oscillation of the Brain

2min

11.

Applications in the Sciences?

3min

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."