AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. - Maria Kalweit; Gabriel Kalweit; Joschka Boedecker (AI4Function@IJCAI, 2021)

Deep Surrogate Q-Learning for Autonomous Driving. - Maria Kalweit; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2022)

Robust and Data-efficient Q-learning by Composite Value-estimation. - Gabriel Kalweit; Maria Kalweit; Joschka Boedecker (Trans. Mach. Learn. Res., 2022)

Deep representations of sets. - Maria Kalweit (2022)

Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. - Mehdi Naouar; Gabriel Kalweit; Ignacio Mastroleo; Philipp Poxleitner; Marc Christian Metzger; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (CoRR, 2023)

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. - Mehdi Naouar; Gabriel Kalweit; Anusha Klett; Yannick Vogt; Paula Silvestrini; Diana Laura Infante Ramírez; Roland Mertelsmann; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs. - Maria Kalweit; Andrea M. Burden; Joschka Boedecker; Thomas Hügle; Theresa Burkard (PLoS Comput. Biol., 2023)

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Roland Mertelsmann; Gabriel Kalweit; Joschka Boedecker (CoRR, 2024)

Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators. - Marieke Wesselkamp; Matthew Chantry; Ewan Pinnington; Margarita Choulga; Souhail Boussetta; Maria Kalweit; Joschka Boedecker; Carsten F. Dormann; Florian Pappenberger; Gianpaolo Balsamo (CoRR, 2024)

BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Joschka Boedecker; Gabriel Kalweit (CoRR, 2024)

Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning. - Paul Schmidt-Barbo; Gabriel Kalweit; Mehdi Naouar; Lisa Paschold; Edith Willscher; Christoph Schultheiß; Bruno Märkl; Stefan Dirnhofer; Alexandar Tzankov; Mascha Binder; Maria Kalweit (PLoS Comput. Biol., 2024)

Multi-intention Inverse Q-learning for Interpretable Behavior Representation. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (Trans. Mach. Learn. Res., 2024)

Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. - Mehdi Naouar; Hanne Raum; Jens Rahnfeld; Yannick Vogt; Joschka Boedecker; Gabriel Kalweit; Maria Kalweit (ICLR, 2025)

Dynamic Robot-Assisted Surgery with Hierarchical Class-Incremental Semantic Segmentation. - Julia Hindel; Ema Mekic; Enamundram Naga Karthik; Rohit Mohan; Daniele Cattaneo 001; Maria Kalweit; Abhinav Valada (CoRR, 2025)