MIC: Mining Interclass Characteristics for Improved Metric Learning. - Biagio Brattoli; Karsten Roth; Björn Ommer (ICCV, 2019)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Eugene Vorontsov; Grzegorz Chlebus; Hao Chen 011; Qi Dou 001; Chi-Wing Fu; Xiao Han; Pheng-Ann Heng; Jürgen Hesser; Samuel Kadoury; Tomasz K. Konopczynski; et al. (CoRR, 2019)

Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function. - Karsten Roth; Tomasz K. Konopczynski; Jürgen Hesser (CoRR, 2019)

Boosting Liver and Lesion Segmentation from CT Scans By Mask Mining. - Karsten Roth; Jürgen Hesser; Tomasz K. Konopczynski (CoRR, 2019)

PADS: Policy-Adapted Sampling for Visual Similarity Learning. - Karsten Roth; Timo Milbich; Björn Ommer (CVPR, 2020)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (ECCV (8), 2020)

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. - Karsten Roth; Timo Milbich; Samarth Sinha; Prateek Gupta; Björn Ommer; Joseph Paul Cohen (ICML, 2020)

Mask Mining for Improved Liver Lesion Segmentation. - Karsten Roth; Jürgen Hesser; Tomasz K. Konopczynski (ISBI, 2020)

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. - Joseph Paul Cohen; Lan Dao; Paul Morrison; Karsten Roth; Yoshua Bengio; Beiyi Shen; Almas Abbasi; Mahsa Hoshmand-Kochi; Marzyeh Ghassemi; Haifang Li; Tim Q. Duong (CoRR, 2020)

COVID-19 Image Data Collection: Prospective Predictions Are the Future. - Joseph Paul Cohen; Paul Morrison; Lan Dao; Karsten Roth; Tim Q. Duong; Marzyeh Ghassemi (CoRR, 2020)

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (CoRR, 2020)

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (ICML, 2021)

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. - Timo Milbich; Karsten Roth; Samarth Sinha; Ludwig Schmidt; Marzyeh Ghassemi; Björn Ommer (NeurIPS, 2021)

Improving the Fairness of Chest X-ray Classifiers. - Haoran Zhang 003; Natalie Dullerud; Karsten Roth; Lauren Oakden-Rayner; Stephen Pfohl; Marzyeh Ghassemi (CHIL, 2022)

Towards Total Recall in Industrial Anomaly Detection. - Karsten Roth; Latha Pemula; Joaquin Zepeda; Bernhard Schölkopf; Thomas Brox; Peter V. Gehler (CVPR, 2022)

Non-isotropy Regularization for Proxy-based Deep Metric Learning. - Karsten Roth; Oriol Vinyals; Zeynep Akata (CVPR, 2022)

Integrating Language Guidance into Vision-based Deep Metric Learning. - Karsten Roth; Oriol Vinyals; Zeynep Akata (CVPR, 2022)

Uniform Priors for Data-Efficient Learning. - Samarth Sinha; Karsten Roth; Anirudh Goyal; Marzyeh Ghassemi; Zeynep Akata; Hugo Larochelle; Animesh Garg (CVPR Workshops, 2022)

A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning. - Michael Kirchhof; Karsten Roth; Zeynep Akata; Enkelejda Kasneci (ECCV (26), 2022)

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. - Natalie Dullerud; Karsten Roth; Kimia Hamidieh; Nicolas Papernot; Marzyeh Ghassemi (ICLR, 2022)

Momentum-based Weight Interpolation of Strong Zero-Shot Models for Continual Learning. - Zafir Stojanovski; Karsten Roth; Zeynep Akata (CoRR, 2022)

Sharing Matters for Generalization in Deep Metric Learning. - Timo Milbich; Karsten Roth; Biagio Brattoli; Björn Ommer (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Waffling around for Performance: Visual Classification with Random Words and Broad Concepts. - Karsten Roth; Jae-Myung Kim; A. Sophia Koepke; Oriol Vinyals; Cordelia Schmid; Zeynep Akata (ICCV, 2023)

Disentanglement of Correlated Factors via Hausdorff Factorized Support. - Karsten Roth; Mark Ibrahim; Zeynep Akata; Pascal Vincent; Diane Bouchacourt (ICLR, 2023)

If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection. - Shyamgopal Karthik; Karsten Roth; Massimiliano Mancini; Zeynep Akata (CoRR, 2023)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Hongwei Li 004; Eugene Vorontsov; Avi Ben-Cohen; Georgios Kaissis; Adi Szeskin; Colin Jacobs; Gabriel Efrain Humpire Mamani; Gabriel Chartrand; Fabian Lohöfer; Julian Walter Holch; et al. (Medical Image Anal., 2023)

Reflecting on the State of Rehearsal-Free Continual Learning with Pretrained Models. - Lukas Thede; Karsten Roth; Olivier J. Hénaff; Matthias Bethge; Zeynep Akata (CoLLAs, 2024)

Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models. - Nishad Singhi; Jae Myung Kim; Karsten Roth; Zeynep Akata (ECCV (26), 2024)

Vision-by-Language for Training-Free Compositional Image Retrieval. - Shyamgopal Karthik; Karsten Roth; Massimiliano Mancini; Zeynep Akata (ICLR, 2024)

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model. - Karsten Roth; Lukas Thede; A. Sophia Koepke; Oriol Vinyals; Olivier J. Hénaff; Zeynep Akata (ICLR, 2024)

ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections. - Massimo Bini; Karsten Roth; Zeynep Akata; Anna Khoreva (ICML, 2024)

ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization. - Luca Eyring; Shyamgopal Karthik; Karsten Roth; Alexey Dosovitskiy; Zeynep Akata (NeurIPS, 2024)

A Practitioner's Guide to Real-World Continual Multimodal Pretraining. - Vishaal Udandarao; Karsten Roth; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Zeynep Akata; Matthias Bethge (NeurIPS, 2024)

Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap. - Théo Uscidda; Luca Eyring; Karsten Roth; Fabian J. Theis; Zeynep Akata; Marco Cuturi (CoRR, 2024)

A Practitioner's Guide to Continual Multimodal Pretraining. - Karsten Roth; Vishaal Udandarao; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Matthias Bethge; Zeynep Akata (CoRR, 2024)

kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies. - Zhongrui Gui; Shuyang Sun; Runjia Li; Jianhao Yuan; Zhaochong An; Karsten Roth; Ameya Prabhu; Philip Torr 001 (Trans. Mach. Learn. Res., 2024)

How to Merge Your Multimodal Models Over Time? - Sebastian Dziadzio; Vishaal Udandarao; Karsten Roth; Ameya Prabhu; Zeynep Akata; Samuel Albanie; Matthias Bethge (CVPR, 2025)

Context-Aware Multimodal Pretraining. - Karsten Roth; Zeynep Akata; Dima Damen; Ivana Balazevic; Olivier J. Hénaff (CVPR, 2025)

Disentangled Representation Learning with the Gromov-Monge Gap. - Théo Uscidda; Luca Eyring; Karsten Roth; Fabian J. Theis; Zeynep Akata; Marco Cuturi (ICLR, 2025)

Understanding the Limits of Lifelong Knowledge Editing in LLMs. - Lukas Thede; Karsten Roth; Matthias Bethge; Zeynep Akata; Tom Hartvigsen (CoRR, 2025)

Subspace-Boosted Model Merging. - Ronald Skorobogat; Karsten Roth; Mariana-Iuliana Georgescu; Zeynep Akata (CoRR, 2025)