Learning representations of irregular particle-detector geometry with distance-weighted graph networks. - Shah Rukh Qasim; Jan Kieseler; Yutaro Iiyama; Maurizio Pierini (CoRR, 2019)

Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph and image data. - Jan Kieseler (CoRR, 2020)

Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics. - Yutaro Iiyama; Gianluca Cerminara; Abhijay Gupta; Jan Kieseler; Vladimir Loncar; Maurizio Pierini; Shah Rukh Qasim; Marcel Rieger; Sioni Summers; Gerrit Van Onsem; Kinga Anna Wozniak; Jennifer Ngadiuba; et al. (Frontiers Big Data, 2020)

End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks. - Shah Rukh Qasim; Nadezda Chernyavskaya; Jan Kieseler; Kenneth Long; Oleksandr Viazlo; Maurizio Pierini; Raheel Nawaz (CoRR, 2022)

Top Quarks from Tevatron to the LHC. - Andreas Jung; Jan Kieseler (Symmetry, 2023)

TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography. - Giles C. Strong; Maxime Lagrange; Aitor Orio; Anna Bordignon; Florian Bury; Tommaso Dorigo; Andrea Giammanco; Mariam Heikal; Jan Kieseler; Max Lamparth; Pablo Martínez Ruíz del Árbol; Federico Nardi; et al. (Mach. Learn. Sci. Technol., 2024)

Constrained Optimization of Charged Particle Tracking with Multi-Agent Reinforcement Learning. - Tobias Kortus; Ralf Keidel; Nicolas R. Gauger; Jan Kieseler (CoRR, 2025)

Neuromorphic Readout for Hadron Calorimeters. - Enrico Lupi; Abhishek; Max Aehle; Muhammad Awais; Alessandro Breccia; Riccardo Carroccio; Long Chen; Abhijit Das; Andrea De Vita; Tommaso Dorigo; Nicolas R. Gauger; Ralf Keidel; et al. (CoRR, 2025)

End-to-End Optimal Detector Design with Mutual Information Surrogates. - Kinga Anna Wozniak; Stephen Mulligan; Jan Kieseler; Markus Klute; François Fleuret; Tobias Golling (CoRR, 2025)