Association mapping in biomedical time series via statistically significant shapelet mining. - Christian Bock; Thomas Gumbsch; Michael Moor; Bastian Rieck; Damian Roqueiro; Karsten M. Borgwardt (Bioinform., 2018)

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. - Bastian Rieck; Matteo Togninalli; Christian Bock; Michael Moor; Max Horn; Thomas Gumbsch; Karsten M. Borgwardt (ICLR (Poster), 2019)

Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. - Michael Moor; Max Horn; Bastian Rieck; Damian Roqueiro; Karsten M. Borgwardt (MLHC, 2019)

Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. - Michael Moor; Max Horn; Bastian Rieck; Damian Roqueiro; Karsten M. Borgwardt (CoRR, 2019)

Machine learning for early prediction of circulatory failure in the intensive care unit. - Stephanie L. Hyland; Martin Faltys; Matthias Hüser; Xinrui Lyu; Thomas Gumbsch; Cristóbal Esteban; Christian Bock; Max Horn; Michael Moor; Bastian Rieck; Marc Zimmermann; Dean A. Bodenham; et al. (CoRR, 2019)

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score. - Zhiliang Wu; Yinchong Yang; Yunpu Ma; Yushan Liu 002; Rui Zhao 011; Michael Moor; Volker Tresp (ICHI, 2020)

Set Functions for Time Series. - Max Horn; Michael Moor; Christian Bock; Bastian Rieck; Karsten M. Borgwardt (ICML, 2020)

Topological Autoencoders. - Michael Moor; Max Horn; Bastian Rieck; Karsten M. Borgwardt (ICML, 2020)

Enhancing statistical power in temporal biomarker discovery through representative shapelet mining. - Thomas Gumbsch; Christian Bock; Michael Moor; Bastian Rieck; Karsten M. Borgwardt (Bioinform., 2020)

Path Imputation Strategies for Signature Models. - Michael Moor; Max Horn; Christian Bock; Karsten M. Borgwardt; Bastian Rieck (CoRR, 2020)

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning. - Christian Bock; Michael Moor; Catherine R. Jutzeler; Karsten M. Borgwardt (Artificial Neural Networks, 3rd Edition, 2021)

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. - Michael Moor; Nicolas Bennett; Drago Plecko; Max Horn; Bastian Rieck; Nicolai Meinshausen; Peter Bühlmann; Karsten M. Borgwardt (CoRR, 2021)

A Survey of Topological Machine Learning Methods. - Felix Hensel; Michael Moor; Bastian Rieck (Frontiers Artif. Intell., 2021)

Topological Graph Neural Networks. - Max Horn; Edward De Brouwer; Michael Moor; Yves Moreau; Bastian Rieck; Karsten M. Borgwardt (ICLR, 2022)

Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients. - Bowen Fan; Juliane Klatt; Michael Moor; Latasha A. Daniels; Philipp K. A Agyeman; Christoph Berger; Eric Giannoni; Martin Stocker; Klara M. Posfay-Barbe; Ulrich Heininger; Sara Bernhard-Stirnemann; Anita Niederer-Loher; et al. (Bioinform., 2022)

Machine Learning on Clinical Time Series: Classification and Representation Learning. - Michael Moor (2022)

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting. - Benjamin Yan; Ruochen Liu; David E. Kuo; Subathra Adithan; Eduardo Pontes Reis; Stephen Kwak; Vasantha Kumar Venugopal; Chloe O'Connell; Agustina Saenz; Pranav Rajpurkar; Michael Moor (EMNLP (Findings), 2023)

Med-Flamingo: a Multimodal Medical Few-shot Learner. - Michael Moor; Qian Huang; Shirley Wu; Michihiro Yasunaga; Yash Dalmia; Jure Leskovec; Cyril Zakka; Eduardo Pontes Reis; Pranav Rajpurkar (ML4H@NeurIPS, 2023)

Zero-shot causal learning. - Hamed Nilforoshan; Michael Moor; Yusuf H. Roohani; Yining Chen; Anja Surina; Michihiro Yasunaga; Sara Oblak; Jure Leskovec (NeurIPS, 2023)

Almanac Copilot: Towards Autonomous Electronic Health Record Navigation. - Cyril Zakka; Joseph Cho; Gracia Fahed; Rohan Shad; Michael Moor; Robyn Fong; Dhamanpreet Kaur; Vishnu Ravi; Oliver O. Aalami; Roxana Daneshjou; Akshay Chaudhari; William Hiesinger (CoRR, 2024)

AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments. - Samuel Schmidgall; Rojin Ziaei; Carl Harris; Eduardo Pontes Reis; Jeffrey Jopling; Michael Moor (CoRR, 2024)

Reverse Image Retrieval Cues Parametric Memory in Multimodal LLMs. - Jialiang Xu; Michael Moor; Jure Leskovec (CoRR, 2024)

AgentRxiv: Towards Collaborative Autonomous Research. - Samuel Schmidgall; Michael Moor (CoRR, 2025)

MIRIAD: Augmenting LLMs with millions of medical query-response pairs. - Qinyue Zheng; Salman Abdullah; Sam Rawal; Cyril Zakka; Sophie Ostmeier; Maximilian Purk; Eduardo Pontes Reis; Eric J. Topol; Jure Leskovec; Michael Moor (CoRR, 2025)

Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards. - Jaehoon Yun; Jiwoong Sohn; Jungwoo Park; Hyunjae Kim; Xiangru Tang; Yanjun Shao; Yonghoe Koo; Minhyeok Ko; Qingyu Chen 001; Mark Gerstein; Michael Moor; Jaewoo Kang (CoRR, 2025)

SMMILE: An Expert-Driven Benchmark for Multimodal Medical In-Context Learning. - Melanie Rieff; Maya Varma; Ossian Rabow; Subathra Adithan; Julie Kim; Ken Chang; Hannah Lee; Nidhi Rohatgi; Christian Bluethgen; Mohamed S. Muneer; Jean-Benoit Delbrouck; Michael Moor (CoRR, 2025)

MARBLE: A Hard Benchmark for Multimodal Spatial Reasoning and Planning. - Yulun Jiang; Yekun Chai; Maria Brbic; Michael Moor (CoRR, 2025)