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Seminar
Seminar: Continual Learning
Manuel Heurich
Comments
This seminar focuses on recent advances in ‘Continual Learning’, an increasingly important field within machine learning. Continual Learning tackles the problem of drifting data in input space and changes between input and target distribution. Static models drop significantly in performance when data distributions are subject to change over time. We will cover recent approaches that tackle this problem from different angles. This seminar explores the training of adaptive models that can perform strongly in highly volatile domains.
close14 Class schedule
Regular appointments
Wed, 2025-04-16 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-04-23 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-04-30 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-05-07 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-05-14 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-05-21 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-05-28 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-06-04 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-06-11 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-06-18 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-06-25 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-07-02 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-07-09 10:00 - 12:00
Seminar: Unsupervised Learning
Wed, 2025-07-16 10:00 - 12:00
Seminar: Unsupervised Learning
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