Luca Eyring

I am an ELLIS PhD student in the Explainable Machine Learning Group at the Technical University of Munich and Helmholtz AI under the supervision of Zeynep Akata and Alexey Dosovitskiy (Inceptive). I am broadly interested in generative modeling, representation learning, and optimal transport.

I pursued a Bachelor in Informatics at LMU Munich and a Master specializing in Machine Learning at Technical University of Munich, during which I was fortunate to partake in a number of research projects. I worked on early-stage Alzheimer’s classification together with the LMU Department of Nuclear Medicine, on Transfer Learning for audio classification under Stephan Günnemann which I continued as a working student at BMW, and completed my Master’s thesis at Helmholtz Munich, supervised by Niki Kilbertus and Fabian Theis.

Selected Publications

2024

ICLR

Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation

Luca Eyring*, Dominik Klein*, Théo Uscidda*, and 4 more authors

In International Conference on Learning Representations (ICLR), 2024

Bib PDF Code

@inproceedings{eyring2024unbalancedness,
  title = {Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation},
  author = {Eyring, Luca and Klein, Dominik and Uscidda, Th{\'e}o and Palla, Giovanni and Kilbertus, Niki and Akata, Zeynep and Theis, Fabian J},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://openreview.net/forum?id=2UnCj3jeao},
}

ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization

Luca Eyring*, Shyamgopal Karthik*, Karsten Roth, and 2 more authors

2024

Bib PDF Code

@article{eyring2024reno,
  title = {ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization},
  author = {Eyring, Luca and Karthik, Shyamgopal and Roth, Karsten and Dosovitskiy, Alexey and Akata, Zeynep},
  year = {2024},
  eprint = {2406.04312},
  archiveprefix = {arXiv},
}