Jannik Kossen

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Active Learning, Bayesian Deep Learning, Transformers

I am a PhD student at the University of Oxford with Tom Rainforth in OxCSML and Yarin Gal in OATML. I am working on (mostly Bayesian) Deep Learning. More specifically, I am currently looking into active learning and self-attention for deep non-parametric models. I received an MSc in Physics from Heidelberg University and have spent time studying in Bremen, Darmstadt, Padova, and at University College London.

I am interested in the societal and ethical implications of AI: I have co-authored a book explaining machine learning to a broad audience, discussed the ethics of AI at the Berlin-Brandenburg Academy of Sciences, and gathered real-world field experience at Bosch.

Publications

2021

• J. Kossen , N. Band , C. Lyle , A. N. Gomez , T. Rainforth , Y. Gal , Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning, Advances in Neural Information Processing Systems, 2021.
  
  @article{kossen2021self,
    title = {{Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning}},
    author = {Kossen, Jannik and Band, Neil and Lyle, Clare and Gomez, Aidan N and Rainforth, Tom and Gal, Yarin},
    journal = {Advances in Neural Information Processing Systems},
    year = {2021}
  }
  

• J. Kossen , S. Farquhar , Y. Gal , T. Rainforth , Active Testing: Sample-Efficient Model Evaluation, International Conference on Machine Learning, 2021.
  
  @article{kossen2021active,
    title = {{Active Testing: Sample-Efficient Model Evaluation}},
    author = {Kossen, Jannik and Farquhar, Sebastian and Gal, Yarin and Rainforth, Tom},
    journal = {International Conference on Machine Learning},
    year = {2021}
  }