Relational Models for Generating Labeled Real-world Graphs. - Christoph Lippert; Nino Shervashidze; Oliver Stegle (MLG/SRL@ILP, 2009)

A kernel method for unsupervised structured network inference. - Christoph Lippert; Oliver Stegle; Zoubin Ghahramani; Karsten M. Borgwardt (AISTATS, 2009)

Gene function prediction from synthetic lethality networks via ranking on demand. - Christoph Lippert; Zoubin Ghahramani; Karsten M. Borgwardt (Bioinform., 2010)

Efficient inference in matrix-variate Gaussian models with iid observation noise. - Oliver Stegle; Christoph Lippert; Joris M. Mooij; Neil D. Lawrence; Karsten M. Borgwardt (NIPS, 2011)

easyGWAS: An integrated interspecies platform for performing genome-wide association studies - Dominik G. Grimm; Bastian Greshake; Stefan Kleeberger; Christoph Lippert; Oliver Stegle; Bernhard Schölkopf; Detlef Weigel; Karsten M. Borgwardt (CoRR, 2012)

It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. - Barbara Rakitsch; Christoph Lippert; Karsten M. Borgwardt; Oliver Stegle (NIPS, 2013)

Detecting regulatory gene-environment interactions with unmeasured environmental factors. - Nicoló Fusi; Christoph Lippert; Karsten M. Borgwardt; Neil D. Lawrence; Oliver Stegle (Bioinform., 2013)

A powerful and efficient set test for genetic markers that handles confounders. - Jennifer Listgarten; Christoph Lippert; Eun Yong Kang; Jing Xiang; Carl Myers Kadie; David Heckerman (Bioinform., 2013)

A Lasso multi-marker mixed model for association mapping with population structure correction. - Barbara Rakitsch; Christoph Lippert; Oliver Stegle; Karsten M. Borgwardt (Bioinform., 2013)

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants. - Christoph Lippert; Jing Xiang; Danilo Horta; Christian Widmer; Carl Myers Kadie; David Heckerman; Jennifer Listgarten (Bioinform., 2014)

Sparse Estimation in a Correlated Probit Model. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; John P. Cunningham; Christoph Lippert; Marius Kloft (CoRR, 2015)

Computational and statistical issues in personalized medicine. - Christoph Lippert; David Heckerman (XRDS, 2015)

Separating Sparse Signals from Correlated Noise in Binary Classification. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; Christoph Lippert; Marius Kloft (CFA@UAI, 2016)

Sparse probit linear mixed model. - Stephan Mandt; Florian Wenzel; Shinichi Nakajima; John P. Cunningham; Christoph Lippert; Marius Kloft (Mach. Learn., 2017)

Integrating omics and MRI data with kernel-based tests and CNNs to identify rare genetic markers for Alzheimer's disease. - Stefan Konigorski; Shahryar Khorasani; Christoph Lippert (CoRR, 2018)

Ensembles of Lasso Screening Rules. - Seunghak Lee; Nico Görnitz; Eric P. Xing; David Heckerman; Christoph Lippert (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Two-sample Testing Using Deep Learning. - Matthias Kirchler; Shahryar Khorasani; Marius Kloft; Christoph Lippert (AISTATS, 2020)

Generative synthetic adversarial network for internal bias correction and handling class imbalance problem in medical image diagnosis. - Mina Rezaei; Tomoki Uemura; Janne Näppi; Hiroyuki Yoshida; Christoph Lippert; Christoph Meinel (Computer-Aided Diagnosis, 2020)

Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties. - Jakob Lindinger; David Reeb; Christoph Lippert; Barbara Rakitsch (NeurIPS, 2020)

3D Self-Supervised Methods for Medical Imaging. - Aiham Taleb; Winfried Loetzsch; Noel Danz; Julius Severin; Thomas Gärtner 004; Benjamin Bergner; Christoph Lippert (NeurIPS, 2020)

Generative multi-adversarial network for striking the right balance in abdominal image segmentation. - Mina Rezaei; Janne J. Näppi; Christoph Lippert; Christoph Meinel; Hiroyuki Yoshida (Int. J. Comput. Assist. Radiol. Surg., 2020)

Multimodal Self-supervised Learning for Medical Image Analysis. - Aiham Taleb; Christoph Lippert; Tassilo Klein; Moin Nabi (IPMI, 2021)

Disentanglement and Local Directions of Variance. - Alexander Rakowski; Christoph Lippert (ECML/PKDD (3), 2021)

Interactive Volumetric Region Growing for Brain Tumor Segmentation on MRI using WebGL. - Jonas Kordt; Paul Brachmann; Daniel Limberger; Christoph Lippert (Web3D, 2021)

Explainability Requires Interactivity. - Matthias Kirchler; Martin Graf; Marius Kloft; Christoph Lippert (CoRR, 2021)

Self-Supervised Learning for 3D Medical Image Analysis using 3D SimCLR and Monte Carlo Dropout. - Yamen Ali; Aiham Taleb; Marina M.-C. Höhne; Christoph Lippert (CoRR, 2021)

Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa. - Jana Fehr; Stefan Konigorski; Stephen Olivier; Resign Gunda; Ashmika Surujdeen; Dickman Gareta; Theresa Smit; Kathy Baisley; Sashen Moodley; Yumna Moosa; Willem Hanekom; Olivier Koole; et al. (npj Digit. Medicine, 2021)

Publisher Correction: Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa. - Jana Fehr; Stefan Konigorski; Stephen Olivier; Resign Gunda; Ashmika Surujdeen; Dickman Gareta; Theresa Smit; Kathy Baisley; Sashen Moodley; Yumna Moosa; Willem Hanekom; Olivier Koole; et al. (npj Digit. Medicine, 2021)

Automatic Detection of Subjective, Annotated and Physiological Stress Responses from Video Data. - Matthias Norden; Oliver T. Wolf; Lennart Lehmann; Katja Langer; Christoph Lippert; Hanna Drimalla (ACII, 2022)

Deep Learning Models for 3D MRI Brain Classification - A Multi-sequence Comparison. - Marius Pullig; Benjamin Bergner; Amish Doshi; Anja Hennemuth; Zahi A. Fayad; Christoph Lippert (Bildverarbeitung für die Medizin, 2022)

ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics. - Aiham Taleb; Matthias Kirchler; Remo Monti; Christoph Lippert (CVPR, 2022)

Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-rays. - Benjamin Bergner; Csaba Rohrer; Aiham Taleb; Martha Duchrau; Guilherme De Leon; Jonas Almeida Rodrigues; Falk Schwendicke; Joachim Krois; Christoph Lippert (MIDL, 2022)

Laplace approximated Gaussian process state-space models. - Jakob Lindinger; Barbara Rakitsch; Christoph Lippert (UAI, 2022)

transferGWAS: GWAS of images using deep transfer learning. - Matthias Kirchler; Stefan Konigorski; Matthias Norden; Christian Meltendorf; Marius Kloft; Claudia Schurmann; Christoph Lippert (Bioinform., 2022)

Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation. - Josafat-Mattias Burmeister; Marcel Fernandez Rosas; Johannes Hagemann; Jonas Kordt; Jasper Blum; Simon Shabo; Benjamin Bergner; Christoph Lippert (CoRR, 2022)

Iterative Patch Selection for High-Resolution Image Recognition. - Benjamin Bergner; Christoph Lippert; Aravindh Mahendran (ICLR, 2023)

Training Normalizing Flows from Dependent Data. - Matthias Kirchler; Christoph Lippert; Marius Kloft (ICML, 2023)

DCID: Deep Canonical Information Decomposition. - Alexander Rakowski; Christoph Lippert (ECML/PKDD (2), 2023)

A Probabilistic Approach to Self-Supervised Learning using Cyclical Stochastic Gradient MCMC. - Masoumeh Javanbakhat; Christoph Lippert (CoRR, 2023)

MixerFlow for Image Modelling. - Eshant English; Matthias Kirchler; Christoph Lippert (CoRR, 2023)

HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes. - Sophie Wharrie; Zhiyu Yang; Vishnu Raj; Remo Monti; Rahul Gupta; Ying Wang 074; Alicia Martin; Luke J. O'Connor; Samuel Kaski; Pekka Marttinen; Pier Francesco Palamara; Christoph Lippert; et al. (Bioinform., 2023)

Kernelised Normalising Flows. - Eshant English; Matthias Kirchler; Christoph Lippert (ICLR, 2024)

Heterogeneous Medical Data Integration with Multi-Source StyleGAN. - Wei-Cheng Lai; Matthias Kirchler; Hadya Yassin; Jana Fehr; Alexander Rakowski; Hampus Olsson; Ludger Starke; Jason Michael Millward; Sonia Waiczies; Christoph Lippert (MIDL, 2024)

Evaluating Age-Related Anatomical Consistency in Synthetic Brain MRI against Real-World Alzheimer's Disease Data. - Hadya Yassin; Jana Fehr; Wei-Cheng Lai; Alina Krichevsky; Alexander Rakowski; Christoph Lippert (MIDL, 2024)

MixerFlow: MLP-Mixer Meets Normalising Flows. - Eshant English; Matthias Kirchler; Christoph Lippert (ECML/PKDD (1), 2024)

Metadata-guided feature disentanglement for functional genomics. - Alexander Rakowski; Remo Monti; Viktoriia Huryn; Marta Lemanczyk; Uwe Ohler; Christoph Lippert (Bioinform., 2024)

Assessing Uncertainty Estimation Methods for 3D Image Segmentation under Distribution Shifts. - Masoumeh Javanbakhat; Md Tasnimul Hasan; Christoph Lippert (CoRR, 2024)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; Christoph Lippert; et al. (CoRR, 2024)

Deep Nonparametric Conditional Independence Tests for Images. - Marco Simnacher; Xiangnan Xu; Hani Park; Christoph Lippert; Sonja Greven (CoRR, 2024)

Conformalised Conditional Normalising Flows for Joint Prediction Regions in time series. - Eshant English; Christoph Lippert (CoRR, 2024)

Quantifying model uncertainty for semantic segmentation of Fluorine-19 MRI using stochastic gradient MCMC. - Masoumeh Javanbakhat; Ludger Starke; Sonia Waiczies; Christoph Lippert (Comput. Vis. Image Underst., 2024)

A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare. - Jana Fehr; Brian Citro; Rohit Malpani; Christoph Lippert; Vince I. Madai (Frontiers Digit. Health, 2024)

Token Cropr: Faster ViTs for Quite a Few Tasks. - Benjamin Bergner; Christoph Lippert; Aravindh Mahendran (CVPR, 2025)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Clara Meister; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; et al. (Trans. Mach. Learn. Res., 2025)

JAPAN: Joint Adaptive Prediction Areas with Normalising-Flows. - Eshant English; Christoph Lippert (CoRR, 2025)

JANET: Joint Adaptive predictioN-region Estimation for Time-series. - Eshant English; Eliot Wong-Toi; Matteo Fontana; Stephan Mandt; Padhraic Smyth; Christoph Lippert (Mach. Learn., 2025)