[IDA ML Seminar] IDA Machine Learning Seminar: Cagatay Yildiz, April 27

Fredrik Lindsten fredrik.lindsten at liu.se
Wed Apr 20 11:56:30 CEST 2022


Dear all,

Due to unforeseen circumstances our speaker scheduled for the IDA ML Seminar on April 27 is unable to travel. Hence, the seminar will be given over Zoom instead. See details below.

Kind regards,
Fredrik



Fredrik Lindsten (LiU) is inviting you to a scheduled Zoom meeting.

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From: Fredrik Lindsten
Sent: den 11 april 2022 10:20
To: ml-seminars at lists.liu.se; idaint at ida.liu.se
Subject: IDA Machine Learning Seminar: Cagatay Yildiz, April 27

Dear all,

We are resuming the IDA Machine Learning Seminar series with on-site talks. The next seminar is on April 27, 15:15-16:15.

Çağatay Yıldız, Department of Computer Science, Aalto University.

Recent advances in black-box models for continuous-time dynamical systems
Abstract: Since the neural ordinary differential equations (ODE) breakthrough, continuous-time dynamical systems have gained enormous popularity. In this talk, we will present a summary of recent advances in black-box continuous-time systems. We will start with the a gentle introduction to ODEs, followed by Gaussian process based, uncertainty-aware ODE systems. Afterwards, we will discuss how to learn stochastic systems using a similar framework. We then explain ODE2VAE, a deep generative second-order ODE model for learning video sequences. Finally, a novel continuous-time model-based reinforcement learning approach will be presented. The presentation will be based on the dissertation here.

Location: Alan Turing, House E, https://www.ida.liu.se/department/location/search.en.shtml?keyword=alan

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The list of future seminars in the series is available at: http://www.ida.liu.se/research/machinelearning/seminars/.
You can subscribe to the seminar series' calendar using this ics link: https://outlook.office365.com/owa/calendar/4d811ae47ce446f58d11a7c2f50a7ed8@ad.liu.se/0f5253d7bc7841248c71eb4c28eb2d668927992292494627279/calendar.ics

Welcome!
IDA Machine Learning Group
Linköping University

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