Karsten Roth

Orcid: 0000-0003-1510-7217

According to our database1, Karsten Roth authored at least 28 papers between 2019 and 2023.

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

Timeline

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Bibliography

2023
The Liver Tumor Segmentation Benchmark (LiTS).
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Medical Image Anal., 2023

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model.
CoRR, 2023

Vision-by-Language for Training-Free Compositional Image Retrieval.
CoRR, 2023

If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection.
CoRR, 2023

Disentanglement of Correlated Factors via Hausdorff Factorized Support.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Waffling around for Performance: Visual Classification with Random Words and Broad Concepts.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Sharing Matters for Generalization in Deep Metric Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Momentum-based Weight Interpolation of Strong Zero-Shot Models for Continual Learning.
CoRR, 2022

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Uniform Priors for Data-Efficient Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Integrating Language Guidance into Vision-based Deep Metric Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Non-isotropy Regularization for Proxy-based Deep Metric Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Total Recall in Industrial Anomaly Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Improving the Fairness of Chest X-ray Classifiers.
Proceedings of the Conference on Health, Inference, and Learning, 2022

2021
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning.
CoRR, 2020

COVID-19 Image Data Collection: Prospective Predictions Are the Future.
CoRR, 2020

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning.
CoRR, 2020

Mask Mining for Improved Liver Lesion Segmentation.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning.
Proceedings of the Computer Vision - ECCV 2020, 2020

PADS: Policy-Adapted Sampling for Visual Similarity Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Boosting Liver and Lesion Segmentation from CT Scans By Mask Mining.
CoRR, 2019

Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function.
CoRR, 2019

The Liver Tumor Segmentation Benchmark (LiTS).
CoRR, 2019

MIC: Mining Interclass Characteristics for Improved Metric Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019


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