Alexej Gossmann

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 27

Top Topics

Unsupervised Clustering

Machine Learning

Prediction Algorithm

Top Venues

Medical Imaging: Image Perception, Observer Performance, and Technology Assessment

Publications

Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner
Is this model reliable for everyone? Testing for strong calibration. AISTATS (2024)
Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio
Monitoring machine learning-based risk prediction algorithms in the presence of performativity. AISTATS (2024)
Xudong Sun, Carla Feistner, Alexej Gossmann, George Schwarz, Rao Muhammad Umer, Lisa Beer, Patrick Rockenschaub, Rahul Babu Shrestha, Armin Gruber, Nutan Chen, Sayedali Shetab Boushehri, Florian Buettner, Carsten Marr
DomainLab: A modular Python package for domain generalization in deep learning. CoRR (2024)
Xudong Sun, Nutan Chen, Alexej Gossmann, Yu Xing, Carla Feistner, Emilio Dorigatt, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling. CoRR (2024)
Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia
Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens. CLeaR (2024)
Jean Feng, Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann
A hierarchical decomposition for explaining ML performance discrepancies. CoRR (2024)
Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia
Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study. CoRR (2023)
Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner
Is this model reliable for everyone? Testing for strong calibration. CoRR (2023)
Mariia Sidulova, Xudong Sun, Alexej Gossmann
Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set. MICCAI (8) (2023)
Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner
Workshop on Applied Data Science for Healthcare: Applications and New Frontiers of Generative Models for Healthcare. KDD (2023)
Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann
Sequential algorithmic modification with test data reuse. UAI (2022)
Jean Feng, Alexej Gossmann, Berkman Sahiner, Romain Pirracchio
Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees. J. Am. Medical Informatics Assoc. 29 (5) (2022)
Tao Xu, Fei Wang, Prithwish Chakraborty, Pei-Yun Sabrina Hsueh, Gregor Stiglic, Jiang Bian, Lixia Yao, Alexej Gossmann, Florian Buettner
Workshop on Applied Data Science for Healthcare (DSHealth): Transparent and Human-centered AI. KDD (2022)
Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions. CoRR (2022)
Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann
Sequential algorithmic modification with test data reuse. CoRR (2022)
Alexej Gossmann, Aria Pezeshk, Yu-Ping Wang, Berkman Sahiner
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve. SIAM J. Math. Data Sci. 3 (2) (2021)
Jean Feng, Alexej Gossmann, Berkman Sahiner, Romain Pirracchio
Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees. CoRR (2021)
Kenny H. Cha, Alexej Gossmann, Nicholas Petrick, Berkman Sahiner
Supplementing training with data from a shifted distribution for machine learning classifiers: adding more cases may not always help. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2020)
Peyman Hosseinzadeh Kassani, Alexej Gossmann, Yu-Ping Wang
Multimodal Sparse Classifier for Adolescent Brain Age Prediction. IEEE J. Biomed. Health Informatics 24 (2) (2020)
Alexej Gossmann, Kenny H. Cha, Xudong Sun
Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift. Medical Imaging: Computer-Aided Diagnosis (2020)
Peyman Hosseinzadeh Kassani, Alexej Gossmann, Yu-Ping Wang
Multimodal Sparse Classifier for Adolescent Brain Age Prediction. CoRR (2019)
Xudong Sun, Yu Wang, Alexej Gossmann, Bernd Bischl
Resampling-based Assessment of Robustness to Distribution Shift for Deep Neural Networks. CoRR (2019)
Xudong Sun, Alexej Gossmann, Yu Wang, Bernd Bischl
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift. SSCI (2019)
Alexej Gossmann, Pascal Zille, Vince D. Calhoun, Yu-Ping Wang
FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics. IEEE Trans. Medical Imaging 37 (8) (2018)
Alexej Gossmann, Aria Pezeshk, Berkman Sahiner
Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed 'test' dataset and a potential solution. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2018)
Alexej Gossmann, Shaolong Cao, Damian Brzyski, Lan-Juan Zhao, Hong-Wen Deng, Yu-Ping Wang
A Sparse Regression Method for Group-Wise Feature Selection with False Discovery Rate Control. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (4) (2018)
Shaolong Cao, Huaizhen Qin, Alexej Gossmann, Hong-Wen Deng, Yu-Ping Wang
Unified tests for fine-scale mapping and identifying sparse high-dimensional sequence associations. Bioinform. 32 (3) (2016)
Alexej Gossmann, Shaolong Cao, Yu-Ping Wang
Identification of significant genetic variants via SLOPE, and its extension to group SLOPE. BCB (2015)
Shaolong Cao, Huaizhen Qin, Alexej Gossmann, Hong-Wen Deng, Yu-Ping Wang
Unified tests for fine scale mapping and identifying sparse high-dimensional sequence associations. BCB (2015)