Lippert, Christoph

25 publications

ICLRW 2025 A Probabilistic Approach to Self-Supervised Learning Using Cyclical Stochastic Gradient MCMC Masoumeh Javanbakhat, Christoph Lippert

MLJ 2025 JANET: Joint Adaptive predictioN-Region Estimation for Time-Series Eshant English, Eliot Wong-Toi, Matteo Fontana, Stephan Mandt, Padhraic Smyth, Christoph Lippert

TMLR 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, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

CVPR 2025 Token Cropr: Faster ViTs for Quite a Few Tasks Benjamin Bergner, Christoph Lippert, Aravindh Mahendran

NeurIPSW 2024 Conformalised Conditional Normalising Flows for Joint Prediction Regions in Time Series Eshant English, 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 Heterogeneous Medical Data Integration with Multi-Source StyleGAN Wei-Cheng Lai, Matthias Kirchler, Hadya Yassin, Jana Fehr, Alexander Rakowski, Hampus Olsson, Ludger Starke, Jason M. Millward, Sonia Waiczies, Christoph Lippert

ICLR 2024 Kernelised Normalising Flows Eshant English, Matthias Kirchler, Christoph Lippert

ECML-PKDD 2024 MixerFlow: MLP-Mixer Meets Normalising Flows Eshant English, Matthias Kirchler, Christoph Lippert

ECML-PKDD 2023 DCID: Deep Canonical Information Decomposition Alexander Rakowski, Christoph Lippert

MIDL 2023 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 Rodrigues, Falk Schwendicke, Joachim Krois, Christoph Lippert

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

ICML 2023 Training Normalizing Flows from Dependent Data Matthias Kirchler, Christoph Lippert, Marius Kloft

CVPR 2022 ContIG: Self-Supervised Multimodal Contrastive Learning for Medical Imaging with Genetics Aiham Taleb, Matthias Kirchler, Remo Monti, Christoph Lippert

NeurIPSW 2022 HAPNEST: An Efficient Tool for Generating Large-Scale Genetics Datasets from Limited Training Data Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J O'Connor, Samuel Kaski, Pekka Marttinen, Pier Palamara, Christoph Lippert, Andrea Ganna

UAI 2022 Laplace Approximated Gaussian Process State-Space Models Jakob Lindinger, Barbara Rakitsch, Christoph Lippert

ECML-PKDD 2021 Disentanglement and Local Directions of Variance Alexander Rakowski, Christoph Lippert

NeurIPS 2020 3D Self-Supervised Methods for Medical Imaging Aiham Taleb, Winfried Loetzsch, Noel Danz, Julius Severin, Thomas Gaertner, Benjamin Bergner, Christoph Lippert

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

AISTATS 2020 Two-Sample Testing Using Deep Learning Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert

MLJ 2017 Sparse Probit Linear Mixed Model Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

UAI 2016 Separating Sparse Signals from Correlated Noise in Binary Classification Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft

NeurIPS 2013 It Is All in the Noise: Efficient Multi-Task Gaussian Process Inference with Structured Residuals Barbara Rakitsch, Christoph Lippert, Karsten Borgwardt, Oliver Stegle

NeurIPS 2011 Efficient Inference in Matrix-Variate Gaussian Models with \iid Observation Noise Oliver Stegle, Christoph Lippert, Joris M. Mooij, Neil D. Lawrence, Karsten Borgwardt

AISTATS 2009 A Kernel Method for Unsupervised Structured Network Inference Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten Borgwardt