Peter Steinbach

According to our database, Peter Steinbach authored at least 20 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Benchmarking Uncertainty Calibration in Large Language Model Long-Form Question Answering.

Philip Müller, Nicholas Popovic, Michael Färber, Peter Steinbach

CoRR, February, 2026

2025

Self-supervised denoising of raw tomography detector data for improved image reconstruction.

Israt Jahan Tulin, Sebastian Starke, Dominic Windisch, André Bieberle, Peter Steinbach

CoRR, November, 2025

Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys.

Alinda Ezgi Gerçek, Till Korten, Paul Chekhonin, Maleeha Hassan, Peter Steinbach

CoRR, November, 2025

Simulation-Based Inference: A Practical Guide.

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

CoRR, August, 2025

sbi reloaded: a toolkit for simulation-based inference workflows.

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

J. Open Source Softw., May, 2025

2024

Training data for "Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power".

Till Korten, Peter Steinbach, Najmeh Mirian

Dataset, November, 2024

mlphys101 - Exploring the performance of Large-Language Models in multilingual undergraduate physics education.

Marcel Völschow, P. Buczek, P. Carreno-Mosquera, C. Mousavias, S. Reganova, E. Roldan-Rodriguez, Peter Steinbach, A. Strube

Dataset, September, 2024

Testing Uncertainty of Large Language Models for Physics Knowledge and Reasoning.

Elizaveta Reganova, Peter Steinbach

CoRR, 2024

Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power.

Till Korten, Vladimir Rybnikov, Mathias Vogt, Juliane Roensch-Schulenburg, Peter Steinbach, Najmeh Mirian

CoRR, 2024

Uncertainty Estimation in Instance Segmentation with Star-convex Shapes.

Qasim M. K. Siddiqui, Sebastian Starke, Peter Steinbach

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Providing AI expertise as an infrastructure in academia.

Marie Piraud, Andrés Camero, Markus Götz, Stefan Kesselheim, Peter Steinbach, Tobias Weigel

Patterns, August, 2023

2022

Recommendations on test datasets for evaluating AI solutions in pathology.

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

CoRR, 2022

Machine Learning State-of-the-Art with Uncertainties.

Peter Steinbach, Felicita Gernhardt, Mahnoor Tanveer, Steve Schmerler, Sebastian Starke

CoRR, 2022

Will the sun shine? - An accessible dataset for teaching machine learning and deep learning.

Florian Huber, Erica Dafne van Kuppevelt, Peter Steinbach, Colin Sauzé, Yang Liu, Berend Weel

Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022

2021

Teaching ML in 2021 - An Overview and Introduction.

Oliver Guhr, Katherine M. Kinnaird, Peter Steinbach

Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, 2021

A Hybrid Radiomics Approach to Modeling Progression-Free Survival in Head and Neck Cancers.

Sebastian Starke, Dominik Thalmeier, Peter Steinbach, Marie Piraud

Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2021

2020

Teaching Machine Learning in 2020.

Peter Steinbach, Heidi Seibold, Oliver Guhr

Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop, 2020

2018

Porting the MPI-parallelised LES model PALM to multi-GPU systems and many integrated core processors - an experience report.

Helge Knoop, Tobias Gronemeier, Matthias Sühring, Peter Steinbach, Matthias Noack, Florian Wende, Thomas Steinke, Christoph Knigge, Siegfried Raasch, Klaus Ketelsen

Int. J. Comput. Sci. Eng., 2018

2016

An automated workflow for parallel processing of large multiview SPIM recordings.

Christopher Schmied, Peter Steinbach, Tobias Pietzsch, Stephan Preibisch, Pavel Tomancak

Bioinform., 2016

Porting the MPI Parallelized LES Model PALM to Multi-GPU Systems - An Experience Report.

Helge Knoop, Tobias Gronemeier, Christoph Knigge, Peter Steinbach

Proceedings of the High Performance Computing, 2016