Sören Dittmer

32 papers Misc 1Journal 27Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events. CoRR Yichen Kelly Chen, Sören Dittmer, Kinga Bernatowicz, Josep Arús-Pous, Kamen Bliznashki, John A. D. Aston, James H. F. Rudd, Carola-Bibiane Schönlieb, James Jones, Michael Roberts
2024	—	`conf`	A Study on the Adequacy of Common IQA Measures for Medical Images. MICAD Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Thomas R. Else, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
2024	J	`jnl`	A study of why we need to reassess full reference image quality assessment with medical images. CoRR Anna Breger, Ander Biguri, Malena Sabaté Landman, Ian Selby, Nicole Amberg, Elisabeth Brunner, Janek Gröhl, Sepideh Hatamikia, Clemens Karner, Lipeng Ning, Sören Dittmer, Michael Roberts, AIX-COVNET Collaboration, Carola-Bibiane Schönlieb
2024	J	`jnl`	A study on the adequacy of common IQA measures for medical images. CoRR Anna Breger, Clemens Karner, Ian Selby, Janek Gröhl, Sören Dittmer, Edward Lilley, Judith Babar, Jake Beckford, Timothy J. Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, Carola-Bibiane Schönlieb
2024	Misc	`conf`	Data-Driven Convex Regularizers for Inverse Problems. ICASSP Subhadip Mukherjee, Sören Dittmer, Zakhar Shumaylov, Sebastian Lunz, Ozan Öktem, Carola B. Schönlieb
2024	J	`jnl`	Equivariant neural operators for gradient-consistent topology optimization. J. Comput. Des. Eng. David Erzmann, Sören Dittmer
2024	J	`jnl`	FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization. CoRR Fan Zhang, Carlos Esteve Yagüe, Sören Dittmer, Carola-Bibiane Schönlieb, Michael Roberts
2024	J	`jnl`	Publisher Correction: The curious case of the test set AUROC. Nat. Mac. Intell. Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2024	J	`jnl`	Recent methodological advances in federated learning for healthcare. Patterns Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, Martijn Schut, Folkert W. Asselbergs, Sujoy Kar, Suthesh Sivapalaratnam, Sophie Williams, Mickey Koh, Yvonne Henskens, Bart de Wit, Umberto D'alessandro, Bubacarr Bah, Ousman Secka, Parashkev Nachev, Rajeev Gupta, Sara Trompeter, Nancy Boeckx, Christine van Laer, Gordon A. Awandare, Kwabena Sarpong, Lucas Amenga-Etego, Mathie P. G. Leers, Mirelle Huijskens, Samuel McDermott, Willem H. Ouwehand, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2024	J	`jnl`	The curious case of the test set AUROC. Nat. Mac. Intell. Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2023	J	`jnl`	Bayesian view on the training of invertible residual networks for solving linear inverse problems. CoRR Clemens Arndt, Sören Dittmer, Nick Heilenkötter, Meira Iske, Tobias Kluth, Judith Nickel
2023	—	`conf`	DL4TO : A Deep Learning Library for Sample-Efficient Topology Optimization. GSI (1) David Erzmann, Sören Dittmer, Henrik Harms, Peter Maaß
2023	J	`jnl`	Invertible residual networks in the context of regularization theory for linear inverse problems. CoRR Clemens Arndt, Alexander Denker, Sören Dittmer, Nick Heilenkötter, Meira Iske, Tobias Kluth, Peter Maass, Judith Nickel
2023	J	`jnl`	Navigating the development challenges in creating complex data systems. Nat. Mac. Intell. Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, Ian Selby, Anna Breger, Matthew Thorpe, Jonathan R. Weir-McCall, Effrossyni Gkrania-Klotsas, Anna Korhonen, Emily R. Jefferson, Georg Langs, Guang Yang, Helmut Prosch, Jan Stanczuk, Jing Tang, Judith Babar, Lorena Escudero Sanchez, Philip Teare, Mishal Patel, Marcel Wassin, Markus Holzer, Nicholas Walton, Pietro Lió, Tolou Shadbahr, Evis Sala, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2023	J	`jnl`	Recent Methodological Advances in Federated Learning for Healthcare. CoRR Fan Zhang, Daniel Kreuter, Yichen Chen, Sören Dittmer, Samuel Tull, Tolou Shadbahr, BloodCounts Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb, Nicholas S. Gleadall, Michael Roberts
2023	J	`jnl`	Reinterpreting survival analysis in the universal approximator age. CoRR Sören Dittmer, Michael Roberts, Jacobus Preller, AIX-COVNET Collaboration, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2023	J	`jnl`	The curious case of the test set AUROC. CoRR Michael Roberts, Alon Hazan, Sören Dittmer, James H. F. Rudd, Carola-Bibiane Schönlieb
2022	J	`jnl`	Classification of datasets with imputed missing values: does imputation quality matter? CoRR Tolou Shadbahr, Michael Roberts, Jan Stanczuk, Julian D. Gilbey, Philip Teare, Sören Dittmer, Matthew Thorpe, Ramón Viñas Torné, Evis Sala, Pietro Lió, Mishal Patel, AIX-COVNET Collaboration, James H. F. Rudd, Tuomas Mirtti, Antti Rannikko, John A. D. Aston, Jing Tang, Carola-Bibiane Schönlieb
2022	J	`jnl`	Navigating the challenges in creating complex data systems: a development philosophy. CoRR Sören Dittmer, Michael Roberts, Julian D. Gilbey, Ander Biguri, AIX-COVNET Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb
2022	J	`jnl`	SELTO: Sample-Efficient Learned Topology Optimization. CoRR Sören Dittmer, David Erzmann, Henrik Harms, Peter Maass
2022	J	`jnl`	Unsupervised Learning of the Total Variation Flow. CoRR Tamara G. Grossmann, Sören Dittmer, Yury Korolev, Carola-Bibiane Schönlieb
2020	—	`conf`	A Deep Prior Approach to Magnetic Particle Imaging. MLMIR@MICCAI Sören Dittmer, Tobias Kluth, Daniel Otero Baguer, Peter Maass
2020	J	`jnl`	Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset. CoRR Sören Dittmer, Tobias Kluth, Mads Thorstein Roar Henriksen, Peter Maass
2020	J	`jnl`	Ground Truth Free Denoising by Optimal Transport. CoRR Sören Dittmer, Carola-Bibiane Schönlieb, Peter Maass
2020	J	`jnl`	Learned convex regularizers for inverse problems. CoRR Subhadip Mukherjee, Sören Dittmer, Zakhar Shumaylov, Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
2020	—	`—`	On deep learning applied to inverse problems: a chicken-and-egg problem. Sören Dittmer
2020	J	`jnl`	Regularization by Architecture: A Deep Prior Approach for Inverse Problems. J. Math. Imaging Vis. Sören Dittmer, Tobias Kluth, Peter Maass, Daniel Otero Baguer
2020	J	`jnl`	Singular Values for ReLU Layers. IEEE Trans. Neural Networks Learn. Syst. Sören Dittmer, Emily J. King, Peter Maass
2019	J	`jnl`	A Projectional Ansatz to Reconstruction. CoRR Sören Dittmer, Peter Maass
2018	J	`jnl`	Analysis of Invariance and Robustness via Invertibility of ReLU-Networks. CoRR Jens Behrmann, Sören Dittmer, Pascal Fernsel, Peter Maaß
2018	J	`jnl`	Regularization by architecture: A deep prior approach for inverse problems. CoRR Sören Dittmer, Tobias Kluth, Peter Maass, Daniel Otero Baguer
2018	J	`jnl`	Singular Values for ReLU Layers. CoRR Sören Dittmer, Emily J. King, Peter Maass