Jannik Kossen
I am a PhD student at the University of Oxford supervised by Tom Rainforth in OxCSML and Yarin Gal in OATML. I am interested in contrastive learning of vision-language models, uncertainties in large language models and computer vision, (vaguely) Bayesian deep learning, active data selection, and 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 was a Student Researcher at Google Research, working on large scale contrastive learning, and a Research Scientist Intern at Deepmind, exploring active feature acquisition for temporal multimodal data.
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
2022
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J. Kossen
,
S. Farquhar
,
Y. Gal
,
T. Rainforth
,
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation, in Advances in Neural Information Processing Systems, 2022.
2021
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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.
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J. Kossen
,
S. Farquhar
,
Y. Gal
,
T. Rainforth
,
Active Testing: Sample-Efficient Model Evaluation, International Conference on Machine Learning, 2021.