Julia Grabinski

Orcid: 0000-0002-8371-1734

According to our database1, Julia Grabinski authored at least 11 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
As large as it gets - Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters.
Trans. Mach. Learn. Res., 2024

Beware of Aliases - Signal Preservation is Crucial for Robust Image Restoration.
CoRR, 2024

Improving Feature Stability During Upsampling - Spectral Artifacts and the Importance of Spatial Context.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Improving Stability during Upsampling - on the Importance of Spatial Context.
CoRR, 2023

As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier Domain.
CoRR, 2023

Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling.
CoRR, 2023

On the unreasonable vulnerability of transformers for image restoration - and an easy fix.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Aliasing and adversarial robust generalization of CNNs.
Mach. Learn., 2022

FrequencyLowCut Pooling - Plug & Play against Catastrophic Overfitting.
CoRR, 2022

Robust Models are less Over-Confident.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FrequencyLowCut Pooling - Plug and Play Against Catastrophic Overfitting.
Proceedings of the Computer Vision - ECCV 2022, 2022


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