[ContinualAI Seminars]: "A Procedural World Generation Framework for Systematic Evaluation of Continual Learning"

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Keiland Cooper

Oct 27, 2021, 8:25:41 AM10/27/21
to Continual Learning & AI News
Hi All,

This Thursday 28-10-2021, 17.30 CEST, for the ContinualAI Seminar, Timm Hess (Goethe University) will present the paper:

Abstract: Several families of continual learning techniques have been proposed to alleviate catastrophic interference in deep neural network training on non-stationary data. However, a comprehensive comparison and analysis of limitations remains largely open due to the inaccessibility to suitable datasets. Empirical examination not only varies immensely between individual works, it further currently relies on contrived composition of benchmarks through subdivision and concatenation of various prevalent static vision datasets. In this work, our goal is to bridge this gap by introducing a computer graphics simulation framework that repeatedly renders only upcoming urban scene fragments in an endless real-time procedural world generation process. At its core lies a modular parametric generative model with adaptable generative factors. The latter can be used to flexibly compose data streams, which significantly facilitates a detailed analysis and allows for effortless investigation of various continual learning schemes.

- YouTube link: [click here and to set up reminders]

- Microsoft Teams: [ click here to join ] 

- YouTube recordings of the previous sessions: https://www.youtube.com/c/ContinualAI

Feel free to share this email to anyone interested and invite them to subscribe this mailing-list here: https://groups.google.com/g/continualai 

Please also contact me if you want to speak at one of the next sessions!

Looking forward to seeing you all there!

All the best,
Keiland Cooper

University of California
ContinualAI Co-founding Board Member

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