Karsten Roth

According to our database, Karsten Roth authored at least 35 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Practitioner's Guide to Continual Multimodal Pretraining.

Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier Hénaff, Samuel Albanie, Matthias Bethge, Zeynep Akata

CoRR, 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

Reflecting on the State of Rehearsal-free Continual Learning with Pretrained Models.

Lukas Thede, Karsten Roth, Olivier J. Hénaff, Matthias Bethge, Zeynep Akata

CoRR, 2024

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

Luca Eyring, Shyamgopal Karthik, Karsten Roth, Alexey Dosovitskiy, 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

CoRR, 2024

ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections.

Massimo Bini, Karsten Roth, Zeynep Akata, Anna Khoreva

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Vision-by-Language for Training-Free Compositional Image Retrieval.

Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models.

Nishad Singhi, Jae Myung Kim, Karsten Roth, Zeynep Akata

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

The Liver Tumor Segmentation Benchmark (LiTS).

Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze

Medical Image Anal., 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

Disentanglement of Correlated Factors via Hausdorff Factorized Support.

Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Sharing Matters for Generalization in Deep Metric Learning.

Timo Milbich, Karsten Roth, Biagio Brattoli, Björn Ommer

IEEE Trans. Pattern Anal. Mach. Intell., 2022

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

Zafir Stojanovski, Karsten Roth, Zeynep Akata

CoRR, 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

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning.

Michael Kirchhof, Karsten Roth, Zeynep Akata, Enkelejda Kasneci

Proceedings of the Computer Vision - ECCV 2022, 2022

Uniform Priors for Data-Efficient Learning.

Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Integrating Language Guidance into Vision-based Deep Metric Learning.

Karsten Roth, Oriol Vinyals, Zeynep Akata

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Non-isotropy Regularization for Proxy-based Deep Metric Learning.

Karsten Roth, Oriol Vinyals, Zeynep Akata

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Total Recall in Industrial Anomaly Detection.

Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Improving the Fairness of Chest X-ray Classifiers.

Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning.

Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer

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.

Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

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

Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi

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

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

Mask Mining for Improved Liver Lesion Segmentation.

Karsten Roth, Jürgen Hesser, Tomasz K. Konopczynski

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.

Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen

Proceedings of the 37th International Conference on Machine Learning, 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

Proceedings of the Computer Vision - ECCV 2020, 2020

PADS: Policy-Adapted Sampling for Visual Similarity Learning.

Karsten Roth, Timo Milbich, Björn Ommer

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.

Karsten Roth, Jürgen Hesser, Tomasz K. Konopczynski

CoRR, 2019

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

Karsten Roth, Tomasz K. Konopczynski, Jürgen Hesser

CoRR, 2019

The Liver Tumor Segmentation Benchmark (LiTS).

Patrick Bilic, Patrick Ferdinand Christ, Eugene Vorontsov, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, Samuel Kadoury, Tomasz K. Konopczynski, Miao Le, Chunming Li, Xiaomeng Li, Jana Lipková, John S. Lowengrub, Hans Meine, Jan Hendrik Moltz, Chris Pal, Marie Piraud, Xiaojuan Qi, Jin Qi, Markus Rempfler, Karsten Roth, Andrea Schenk, Anjany Sekuboyina, Ping Zhou, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Felix Grün, Georgios Kaissis, Fabian Lohöfer, Rickmer Braren, Julian Holch, Felix Hofmann, Wieland H. Sommer, Volker Heinemann, Colin Jacobs, Gabriel Efrain Humpire Mamani, Bram van Ginneken, Gabriel Chartrand, An Tang, Michal Drozdzal, Avi Ben-Cohen, Eyal Klang, Michal Marianne Amitai, Eli Konen, Hayit Greenspan, Johan Moreau, Alexandre Hostettler, Luc Soler, Refael Vivanti, Adi Szeskin, Naama Lev-Cohain, Jacob Sosna, Leo Joskowicz, Bjoern H. Menze

CoRR, 2019

MIC: Mining Interclass Characteristics for Improved Metric Learning.

Biagio Brattoli, Karsten Roth, Björn Ommer

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019