Peter Steinbach

23 papers A 1Journal 14Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Benchmarking Uncertainty Calibration in Large Language Model Long-Form Question Answering. CoRR Philip Müller, Nicholas Popovic, Michael Färber, Peter Steinbach
2025	J	`jnl`	Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys. CoRR Alinda Ezgi Gerçek, Till Korten, Paul Chekhonin, Maleeha Hassan, Peter Steinbach
2025	J	`jnl`	Self-supervised denoising of raw tomography detector data for improved image reconstruction. CoRR Israt Jahan Tulin, Sebastian Starke, Dominic Windisch, André Bieberle, Peter Steinbach
2025	J	`jnl`	Simulation-Based Inference: A Practical Guide. CoRR Michael Deistler, Jan Boelts, Peter Steinbach, Guy Moss, Thomas Moreau, Manuel Glöckler, Pedro L. C. Rodrigues, Julia Linhart, Janne K. Lappalainen, Benjamin Kurt Miller, Pedro J. Gonçalves, Jan-Matthis Lueckmann, Cornelius Schröder, Jakob H. Macke
2025	J	`jnl`	sbi reloaded: a toolkit for simulation-based inference workflows. J. Open Source Softw. Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2024	J	`jnl`	Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power. CoRR Till Korten, Vladimir Rybnikov, Mathias Vogt, Juliane Roensch-Schulenburg, Peter Steinbach, Najmeh Mirian
2024	J	`jnl`	Testing Uncertainty of Large Language Models for Physics Knowledge and Reasoning. CoRR Elizaveta Reganova, Peter Steinbach
2024	A	`conf`	Uncertainty Estimation in Instance Segmentation with Star-convex Shapes. WACV Qasim M. K. Siddiqui, Sebastian Starke, Peter Steinbach
2024	J	`jnl`	sbi reloaded: a toolkit for simulation-based inference workflows. CoRR Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2023	J	`jnl`	Providing AI expertise as an infrastructure in academia. Patterns Marie Piraud, Andrés Camero, Markus Götz, Stefan Kesselheim, Peter Steinbach, Tobias Weigel
2023	J	`jnl`	Uncertainty Estimation in Instance Segmentation with Star-convex Shapes. CoRR Qasim M. K. Siddiqui, Sebastian Starke, Peter Steinbach
2022	J	`jnl`	Machine Learning State-of-the-Art with Uncertainties. CoRR Peter Steinbach, Felicita Gernhardt, Mahnoor Tanveer, Steve Schmerler, Sebastian Starke
2022	J	`jnl`	Recommendations on test datasets for evaluating AI solutions in pathology. CoRR André Homeyer, Christian Geißler, Lars Ole Schwen, Falk Zakrzewski, Theodore Evans, Klaus Strohmenger, Max Westphal, Roman David Bülow, Michaela Kargl, Aray Karjauv, Isidre Munné-Bertran, Carl Orge Retzlaff, Adrià Romero-López, Tomasz Soltysinski, Markus Plass, Rita Carvalho, Peter Steinbach, Yu-Chia Lan, Nassim Bouteldja, David Haber, Mateo Rojas-Carulla, Alireza Vafaei Sadr, Matthias Kraft, Daniel Krüger, Rutger Fick, Tobias Lang, Peter Boor, Heimo Müller, Peter Hufnagl, Norman Zerbe
2022	—	`ed.`	The Third Teaching Machine Learning and Artificial Intelligence Workshop, 19-23 September 2022, Grenoble, France and online. Teaching ML Katherine M. Kinnaird, Peter Steinbach, Oliver Guhr
2022	—	`conf`	Will the sun shine? - An accessible dataset for teaching machine learning and deep learning. Teaching ML Florian Huber, Erica Dafne van Kuppevelt, Peter Steinbach, Colin Sauzé, Yang Liu, Berend Weel
2021	—	`conf`	A Hybrid Radiomics Approach to Modeling Progression-Free Survival in Head and Neck Cancers. HECKTOR@MICCAI Sebastian Starke, Dominik Thalmeier, Peter Steinbach, Marie Piraud
2021	—	`ed.`	Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, September 8+13, 2021, Virtual Conference. Teaching ML Katherine M. Kinnaird, Peter Steinbach, Oliver Guhr
2021	—	`conf`	Teaching ML in 2021 - An Overview and Introduction. Teaching ML Oliver Guhr, Katherine M. Kinnaird, Peter Steinbach
2020	—	`ed.`	Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop, September 8+14, 2020, Virtual Conference. Teaching ML Bernd Bischl, Oliver Guhr, Heidi Seibold, Peter Steinbach
2020	—	`conf`	Teaching Machine Learning in 2020. Teaching ML Peter Steinbach, Heidi Seibold, Oliver Guhr
2018	J	`jnl`	Porting the MPI-parallelised LES model PALM to multi-GPU systems and many integrated core processors - an experience report. Int. J. Comput. Sci. Eng. Helge Knoop, Tobias Gronemeier, Matthias Sühring, Peter Steinbach, Matthias Noack, Florian Wende, Thomas Steinke, Christoph Knigge, Siegfried Raasch, Klaus Ketelsen
2016	J	`jnl`	An automated workflow for parallel processing of large multiview SPIM recordings. Bioinform. Christopher Schmied, Peter Steinbach, Tobias Pietzsch, Stephan Preibisch, Pavel Tomancak
2016	—	`conf`	Porting the MPI Parallelized LES Model PALM to Multi-GPU Systems - An Experience Report. ISC Workshops Helge Knoop, Tobias Gronemeier, Christoph Knigge, Peter Steinbach