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ML Methods dealing with Robustness, Adversarial Attacks. Working with Graphical and Temporal Data. Part of coursework Lecture: Machine Learning for Graphs and Sequential Data

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ML-For-Graphs-and-Sequential-Data

ML Methods dealing with Robustness, Adversarial Attacks. Working with Graphical and Temporal Data. Part of coursework Lecture: Machine Learning for Graphs and Sequential Data

Project 1a: Normalizing Flows

Project 1b: Variational Autoencoders

Project 2: Robustness of Machine Learning Models

Project 3: Word2Vec (Natural Language Processing example)

Project 4: Spectral Clustering

Project 5: Graph Neural Networks

Solutions private. Available on Request. Course Website: https://www.in.tum.de/en/daml/teaching/summer-term-2020/machine-learning-for-graphs-and-sequential-data/

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ML Methods dealing with Robustness, Adversarial Attacks. Working with Graphical and Temporal Data. Part of coursework Lecture: Machine Learning for Graphs and Sequential Data

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