Long Term Time Series Forecasting

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."

Guests

Alex Mallen: Alex Mallen is an undergraduate student at the University of Washington studying Computer Science. He is interested in math and its applications in neuroscience and machine learning, and has conducted research in machine learning algorithms and the mammalian visual system.

Henning Lange: Henning received his BSc in Cognitive Science from the University of Osnabrueck, Germany, in 2012, an MSc in Machine Learning from Aalto University, Finland, in 2016 and a PhD in Advanced Infrastructure System from Carnegie Mellon University in 2019. He currently serves as a postdoctoral scholar in the Applied Maths department at the University of Washington under supervision of Nathan Kutz.