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Karsten Roth
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2020 – today
- 2024
- [c20]Nishad Singhi, Jae Myung Kim, Karsten Roth, Zeynep Akata:
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models. ECCV (26) 2024: 422-438 - [c19]Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata:
Vision-by-Language for Training-Free Compositional Image Retrieval. ICLR 2024 - [c18]Karsten Roth, Lukas Thede, A. Sophia Koepke, Oriol Vinyals, Olivier J. Hénaff, Zeynep Akata:
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model. ICLR 2024 - [c17]Massimo Bini, Karsten Roth, Zeynep Akata, Anna Khoreva:
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections. ICML 2024 - [i31]Zhongrui Gui, Shuyang Sun, Runjia Li, Jianhao Yuan, Zhaochong An, Karsten Roth, Ameya Prabhu, Philip Torr:
kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies. CoRR abs/2404.09447 (2024) - [i30]Nishad Singhi, Jae-Myung Kim, Karsten Roth, Zeynep Akata:
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models. CoRR abs/2405.01531 (2024) - [i29]Massimo Bini, Karsten Roth, Zeynep Akata, Anna Khoreva:
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections. CoRR abs/2405.20271 (2024) - [i28]Luca Eyring, Shyamgopal Karthik, Karsten Roth, Alexey Dosovitskiy, Zeynep Akata:
ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization. CoRR abs/2406.04312 (2024) - [i27]Lukas Thede, Karsten Roth, Olivier J. Hénaff, Matthias Bethge, Zeynep Akata:
Reflecting on the State of Rehearsal-free Continual Learning with Pretrained Models. CoRR abs/2406.09384 (2024) - [i26]Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J. Theis, Zeynep Akata, Marco Cuturi:
Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap. CoRR abs/2407.07829 (2024) - [i25]Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, Ameya Prabhu, Mehdi Cherti, Oriol Vinyals, Olivier Hénaff, Samuel Albanie, Matthias Bethge, Zeynep Akata:
A Practitioner's Guide to Continual Multimodal Pretraining. CoRR abs/2408.14471 (2024) - 2023
- [j2]Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li
, Eugene Vorontsov
The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Anal. 84: 102680 (2023) - [c16]Karsten Roth, Jae-Myung Kim, A. Sophia Koepke, Oriol Vinyals, Cordelia Schmid, Zeynep Akata:
Waffling around for Performance: Visual Classification with Random Words and Broad Concepts. ICCV 2023: 15700-15711 - [c15]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. ICLR 2023 - [i24]Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata:
If at First You Don't Succeed, Try, Try Again: Faithful Diffusion-based Text-to-Image Generation by Selection. CoRR abs/2305.13308 (2023) - [i23]Karsten Roth, Jae-Myung Kim, A. Sophia Koepke, Oriol Vinyals, Cordelia Schmid, Zeynep Akata:
Waffling around for Performance: Visual Classification with Random Words and Broad Concepts. CoRR abs/2306.07282 (2023) - [i22]Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata:
Vision-by-Language for Training-Free Compositional Image Retrieval. CoRR abs/2310.09291 (2023) - [i21]Karsten Roth, Lukas Thede, Almut Sophia Koepke, Oriol Vinyals, Olivier J. Hénaff, Zeynep Akata:
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model. CoRR abs/2310.17653 (2023) - 2022
- [j1]Timo Milbich
Sharing Matters for Generalization in Deep Metric Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(1): 416-427 (2022) - [c14]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CHIL 2022: 204-233 - [c13]Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg:
Uniform Priors for Data-Efficient Learning. CVPR Workshops 2022: 4016-4027 - [c12]Karsten Roth, Oriol Vinyals, Zeynep Akata:
Non-isotropy Regularization for Proxy-based Deep Metric Learning. CVPR 2022: 7410-7420 - [c11]Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler:
Towards Total Recall in Industrial Anomaly Detection. CVPR 2022: 14298-14308 - [c10]Karsten Roth, Oriol Vinyals, Zeynep Akata:
Integrating Language Guidance into Vision-based Deep Metric Learning. CVPR 2022: 16156-16168 - [c9]Michael Kirchhof
A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning. ECCV (26) 2022: 435-454 - [c8]Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi:
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. ICLR 2022 - [i20]Karsten Roth, Oriol Vinyals, Zeynep Akata:
Integrating Language Guidance into Vision-based Deep Metric Learning. CoRR abs/2203.08543 (2022) - [i19]Karsten Roth, Oriol Vinyals, Zeynep Akata:
Non-isotropy Regularization for Proxy-based Deep Metric Learning. CoRR abs/2203.08547 (2022) - [i18]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl
Improving the Fairness of Chest X-ray Classifiers. CoRR abs/2203.12609 (2022) - [i17]Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi:
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. CoRR abs/2203.12748 (2022) - [i16]Michael Kirchhof, Karsten Roth, Zeynep Akata, Enkelejda Kasneci:
A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning. CoRR abs/2207.03784 (2022) - [i15]Karsten Roth, Mark Ibrahim, Zeynep Akata, Pascal Vincent, Diane Bouchacourt:
Disentanglement of Correlated Factors via Hausdorff Factorized Support. CoRR abs/2210.07347 (2022) - [i14]Zafir Stojanovski, Karsten Roth, Zeynep Akata:
Momentum-based Weight Interpolation of Strong Zero-Shot Models for Continual Learning. CoRR abs/2211.03186 (2022) - 2021
- [c7]Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi:
Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. ICML 2021: 9095-9106 - [c6]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. NeurIPS 2021: 25006-25018 - [i13]Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter V. Gehler:
Towards Total Recall in Industrial Anomaly Detection. CoRR abs/2106.08265 (2021) - [i12]Timo Milbich, Karsten Roth, Samarth Sinha, Ludwig Schmidt, Marzyeh Ghassemi, Björn Ommer:
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. CoRR abs/2107.09562 (2021) - 2020
- [c5]Karsten Roth, Timo Milbich, Björn Ommer:
PADS: Policy-Adapted Sampling for Visual Similarity Learning. CVPR 2020: 6567-6576 - [c4]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. ECCV (8) 2020: 590-607 - [c3]Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen:
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. ICML 2020: 8242-8252 - [c2]Karsten Roth, Jürgen Hesser, Tomasz K. Konopczynski:
Mask Mining for Improved Liver Lesion Segmentation. ISBI 2020: 943-947 - [i11]Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen:
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. CoRR abs/2002.08473 (2020) - [i10]Karsten Roth, Timo Milbich, Björn Ommer:
PADS: Policy-Adapted Sampling for Visual Similarity Learning. CoRR abs/2003.11113 (2020) - [i9]Timo Milbich, Karsten Roth, Biagio Brattoli, Björn Ommer:
Sharing Matters for Generalization in Deep Metric Learning. CoRR abs/2004.05582 (2020) - [i8]Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha, Yoshua Bengio, Björn Ommer, Joseph Paul Cohen:
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. CoRR abs/2004.13458 (2020) - [i7]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:
Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning. CoRR abs/2005.11856 (2020) - [i6]Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q. Duong, Marzyeh Ghassemi:
COVID-19 Image Data Collection: Prospective Predictions Are the Future. CoRR abs/2006.11988 (2020) - [i5]Karsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi:
S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. CoRR abs/2009.08348 (2020)
2010 – 2019
- 2019
- [c1]Biagio Brattoli, Karsten Roth, Björn Ommer:
MIC: Mining Interclass Characteristics for Improved Metric Learning. ICCV 2019: 7999-8008 - [i4]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
The Liver Tumor Segmentation Benchmark (LiTS). CoRR abs/1901.04056 (2019) - [i3]Karsten Roth, Tomasz K. Konopczynski, Jürgen Hesser:
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function. CoRR abs/1905.03639 (2019) - [i2]Karsten Roth, Jürgen Hesser, Tomasz K. Konopczynski:
Boosting Liver and Lesion Segmentation from CT Scans By Mask Mining. CoRR abs/1908.05062 (2019) - [i1]Karsten Roth, Biagio Brattoli, Björn Ommer:
MIC: Mining Interclass Characteristics for Improved Metric Learning. CoRR abs/1909.11574 (2019)
Coauthor Index
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last updated on 2024-11-15 19:31 CET by the dblp team
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