Lukas Gosch

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Hello, welcome to my corner of the web!

I am a researcher focusing on robust and reliable machine learning, as well as machine learning on graphs. I am doing my PhD at TU Munich under the supervision of Prof. Günnemann in the DAML research group and am part of the relAI graduate school. Currently, I am especially interested in provable robustness. Furthermore, I am also interested in theoretical machine learning, uncertainty quantification, and combinatorial optimization.

If you want to contact me, best write me an e-mail: lukas . gosch [at] tum.de. Scroll down to find my other social media appearances.

Quick Link: Resume/CV

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selected publications

  1. Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
    Lukas Gosch, Simon Geisler, Daniel Sturm, and 3 more authors
    In Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023
  2. Revisiting Robustness in Graph Machine Learning
    Lukas Gosch, Daniel Sturm, Simon Geisler, and 1 more author
    In The Eleventh International Conference on Learning Representations (ICLR), 2023