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

NeurIPS

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

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

In Neural Information Processing Systems (NeurIPS), 2024

Bib PDF Demo Code

@inproceedings{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},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  demo = {https://huggingface.co/spaces/fffiloni/ReNO}
}

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 Talk 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},
}