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ORCIDMina Rezaei
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2020 – today
- 2024
[c21]JaeEun Nam, Ilias Chalkidis, Mina Rezaei:
Hyperbolic Contrastive Learning for Document Representations - A Multi-View Approach with Paragraph-level Similarities. ECAI 2024: 1656-1663- [c20]Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. ICLR 2024 - [c19]Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz:
Uncertainty-Aware Vision Transformers for Medical Image Analysis. UNSURE@MICCAI 2024: 171-180 - [c18]Amihossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Diversified Ensemble of Independent Sub-networks for Robust Self-supervised Representation Learning. ECML/PKDD (1) 2024: 38-55 - [c17]Fabian Stermann, Ilias Chalkidis, Amihossein Vahidi, Bernd Bischl, Mina Rezaei:
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings. ECML/PKDD (1) 2024: 89-106 - [i23]Yang Zhang, Yawei Li, Xinpeng Wang, Qianli Shen, Barbara Plank, Bernd Bischl, Mina Rezaei, Kenji Kawaguchi:
FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models. CoRR abs/2405.18218 (2024) - 2023
- [j3]Mina Rezaei
, Farzin Soleymani, Bernd Bischl, Shekoofeh Azizi:
Deep Bregman divergence for self-supervised representations learning. Comput. Vis. Image Underst. 235: 103801 (2023) - [c16]Daniel Saggau, Mina Rezaei, Bernd Bischl, Ilias Chalkidis:
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning. ACL (Findings) 2023: 12181-12190 - [c15]Amadeu Scheppach, Hüseyin Anil Gündüz, Emilio Dorigatti, Philipp C. Münch, Alice C. McHardy, Bernd Bischl, Mina Rezaei, Martin Binder:
Neural Architecture Search for Genomic Sequence Data. CIBCB 2023: 1-10 - [c14]Hüseyin Anil Gündüz, Sheetal Giri, Martin Binder, Bernd Bischl, Mina Rezaei:
Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences. ICMLA 2023: 566-573 - [i22]Mina Rezaei, Patsy Eubanks Owens:
Young Humans Make Change, Young Users Click: Creating Youth-Centered Networked Social Movements. CoRR abs/2303.07541 (2023) - [i21]Daniel Saggau, Mina Rezaei, Bernd Bischl, Ilias Chalkidis:
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning. CoRR abs/2305.16031 (2023) - [i20]Yawei Li, Yang Zhang, Kenji Kawaguchi, Ashkan Khakzar, Bernd Bischl, Mina Rezaei:
A Dual-Perspective Approach to Evaluating Feature Attribution Methods. CoRR abs/2308.08949 (2023) - [i19]Amirhossein Vahidi, Lisa Wimmer, Hüseyin Anil Gündüz, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning. CoRR abs/2308.14705 (2023) - [i18]Amirhossein Vahidi, Simon Schoßer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hüllermeier, Mina Rezaei:
Probabilistic Self-supervised Learning via Scoring Rules Minimization. CoRR abs/2309.02048 (2023) - [i17]Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei, Bernd Bischl, Philip H. S. Torr, Ashkan Khakzar, Kenji Kawaguchi:
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments. CoRR abs/2310.06514 (2023) - [i16]Franciskus Xaverius Erick, Mina Rezaei, Johanna Paula Müller, Bernhard Kainz:
Stochastic Vision Transformers with Wasserstein Distance-Aware Attention. CoRR abs/2311.18645 (2023) - 2022
- [c13]Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl:
Joint Debiased Representation Learning and Imbalanced Data Clustering. ICDM (Workshops) 2022: 55-62 - [c12]Mina Rezaei, Janne J. Näppi, Bernd Bischl, Hiroyuki Yoshida:
Bayesian uncertainty estimation for detection of long-tail and unseen conditions in abdominal images. Medical Imaging: Computer-Aided Diagnosis 2022 - [c11]Farzin Soleymani, Mohammad Eslami, Tobias Elze, Bernd Bischl, Mina Rezaei:
Deep variational clustering framework for self-labeling large-scale medical images. Medical Imaging: Image Processing 2022 - [c10]Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz, Mina Rezaei, Bernd Bischl, Rodrigo Caye Daudt, Stefano D'Aronco, Jan D. Wegner, Konrad Schindler:
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation. NeurIPS 2022 - [i15]Emilio Dorigatti, Jann Goschenhofer, Benjamin Schubert, Mina Rezaei, Bernd Bischl:
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection. CoRR abs/2201.13192 (2022) - [i14]Ashkan Khakzar, Yawei Li, Yang Zhang, Mirac Sanisoglu, Seong Tae Kim, Mina Rezaei, Bernd Bischl, Nassir Navab:
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models. CoRR abs/2204.01729 (2022) - [i13]Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz, Mina Rezaei, Bernd Bischl, Rodrigo Caye Daudt, Stefano D'Aronco, Jan Dirk Wegner, Konrad Schindler:
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation. CoRR abs/2206.00050 (2022) - [i12]Emilio Dorigatti, Jonas Schweisthal, Bernd Bischl, Mina Rezaei:
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision. CoRR abs/2209.02459 (2022) - [i11]Mina Rezaei, Patsy Eubanks Owens, Darnel Degand:
Evaluating User Experience in Literary and Film Geography-based Apps with a Cartographical User-Centered Design Lens. CoRR abs/2209.05734 (2022) - [i10]Shunjie-Fabian Zheng, JaeEun Nam, Emilio Dorigatti, Bernd Bischl, Shekoofeh Azizi, Mina Rezaei:
Joint Debiased Representation and Image Clustering Learning with Self-Supervision. CoRR abs/2209.06941 (2022) - 2021
- [i9]Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl:
Learning Statistical Representation with Joint Deep Embedded Clustering. CoRR abs/2109.05232 (2021) - [i8]Mina Rezaei, Farzin Soleymani, Bernd Bischl, Shekoofeh Azizi:
Deep Bregman Divergence for Contrastive Learning of Visual Representations. CoRR abs/2109.07455 (2021) - [i7]Farzin Soleymani, Mohammad Eslami, Tobias Elze, Bernd Bischl, Mina Rezaei:
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images. CoRR abs/2109.10777 (2021) - 2020
- [j2]Mina Rezaei, Janne J. Näppi, Christoph Lippert, Christoph Meinel, Hiroyuki Yoshida:
Generative multi-adversarial network for striking the right balance in abdominal image segmentation. Int. J. Comput. Assist. Radiol. Surg. 15(11): 1847-1858 (2020) - [j1]Mina Rezaei, Haojin Yang, Christoph Meinel:
Recurrent generative adversarial network for learning imbalanced medical image semantic segmentation. Multim. Tools Appl. 79(21-22): 15329-15348 (2020) - [c9]Mina Rezaei, Tomoki Uemura, Janne Näppi, Hiroyuki Yoshida, Christoph Lippert, Christoph Meinel:
Generative synthetic adversarial network for internal bias correction and handling class imbalance problem in medical image diagnosis. Medical Imaging: Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [b1]Mina Rezaei:
Deep representation learning from imbalanced medical imaging. University of Potsdam, Germany, 2019 - [c8]Mina Rezaei, Haojin Yang, Christoph Meinel:
Learning imbalanced semantic segmentation through cross-domain relations of multi-agent generative adversarial networks. Medical Imaging: Computer-Aided Diagnosis 2019: 1095027 - [c7]Mina Rezaei, Haojin Yang, Konstantin Harmuth, Christoph Meinel:
Conditional Generative Adversarial Refinement Networks for Unbalanced Medical Image Semantic Segmentation. WACV 2019: 1836-1845 - 2018
- [c6]Mina Rezaei, Haojin Yang, Christoph Meinel:
Whole Heart and Great Vessel Segmentation with Context-aware of Generative Adversarial Networks. Bildverarbeitung für die Medizin 2018: 353-358 - [c5]Mina Rezaei, Haojin Yang, Christoph Meinel:
Generative Adversarial Framework for Learning Multiple Clinical Tasks. DICTA 2018: 1-8 - [c4]Mina Rezaei, Haojin Yang, Christoph Meinel:
Instance Tumor Segmentation using Multitask Convolutional Neural Network. IJCNN 2018: 1-8 - [c3]Mina Rezaei, Haojin Yang, Christoph Meinel:
voxel-GAN: Adversarial Framework for Learning Imbalanced Brain Tumor Segmentation. BrainLes@MICCAI (2) 2018: 321-333 - [i6]Mina Rezaei, Haojin Yang, Christoph Meinel:
Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation. CoRR abs/1810.03871 (2018) - [i5]Mina Rezaei, Haojin Yang, Christoph Meinel:
Multi-Task Generative Adversarial Network for Handling Imbalanced Clinical Data. CoRR abs/1811.10419 (2018) - 2017
- [c2]Mina Rezaei, Haojin Yang, Christoph Meinel:
Deep Neural Network with l2-Norm Unit for Brain Lesions Detection. ICONIP (4) 2017: 798-807 - [c1]Mina Rezaei, Konstantin Harmuth, Willi Gierke, Thomas Kellermeier, Martin Fischer, Haojin Yang, Christoph Meinel:
A Conditional Adversarial Network for Semantic Segmentation of Brain Tumor. BrainLes@MICCAI 2017: 241-252 - [i4]Mina Rezaei, Haojin Yang, Christoph Meinel:
Brain Abnormality Detection by Deep Convolutional Neural Network. CoRR abs/1708.05206 (2017) - [i3]Mina Rezaei, Haojin Yang, Christoph Meinel:
Deep Neural Network with l2-norm Unit for Brain Lesions Detection. CoRR abs/1708.05221 (2017) - [i2]Mina Rezaei, Konstantin Harmuth, Willi Gierke, Thomas Kellermeier, Martin Fischer, Haojin Yang, Christoph Meinel:
Conditional Adversarial Network for Semantic Segmentation of Brain Tumor. CoRR abs/1708.05227 (2017) - [i1]Mina Rezaei, Haojin Yang, Christoph Meinel:
Deep Learning for Medical Image Analysis. CoRR abs/1708.08987 (2017)
Coauthor Index
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last updated on 2024-10-28 20:11 CET by the dblp team
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