Christoph Lippert

Orcid: 0000-0001-6363-2556

Affiliations:
  • Hasso Plattner Institute, Potsdam, Germany
  • Hasso Plattner Institute for Digital Health at Mount Sinai (HPI-MS), New York, NY, USA


According to our database1, Christoph Lippert authored at least 47 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare.
Frontiers Digit. Health, 2024

Quantifying model uncertainty for semantic segmentation of Fluorine-19 MRI using stochastic gradient MCMC.
Comput. Vis. Image Underst., 2024

JANET: Joint Adaptive predictioN-region Estimation for Time-series.
CoRR, 2024

On the Challenges and Opportunities in Generative AI.
CoRR, 2024

Assessing Uncertainty Estimation Methods for 3D Image Segmentation under Distribution Shifts.
CoRR, 2024

MixerFlow: MLP-Mixer Meets Normalising Flows.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Kernelised Normalising Flows.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes.
Bioinform., September, 2023

MixerFlow for Image Modelling.
CoRR, 2023

A Probabilistic Approach to Self-Supervised Learning using Cyclical Stochastic Gradient MCMC.
CoRR, 2023

DCID: Deep Canonical Information Decomposition.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Training Normalizing Flows from Dependent Data.
Proceedings of the International Conference on Machine Learning, 2023

Iterative Patch Selection for High-Resolution Image Recognition.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation.
CoRR, 2022

transferGWAS: GWAS of images using deep transfer learning.
Bioinform., 2022

Laplace approximated Gaussian process state-space models.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-rays.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

ContIG: Self-supervised Multimodal Contrastive Learning for Medical Imaging with Genetics.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Deep Learning Models for 3D MRI Brain Classification - A Multi-sequence Comparison.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Automatic Detection of Subjective, Annotated and Physiological Stress Responses from Video Data.
Proceedings of the 10th International Conference on Affective Computing and Intelligent Interaction, 2022

2021
Publisher Correction: Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa.
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npj Digit. Medicine, 2021

Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa.
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npj Digit. Medicine, 2021

Self-Supervised Learning for 3D Medical Image Analysis using 3D SimCLR and Monte Carlo Dropout.
CoRR, 2021

Explainability Requires Interactivity.
CoRR, 2021

Interactive Volumetric Region Growing for Brain Tumor Segmentation on MRI using WebGL.
Proceedings of the Web3D '21: The 26th International Conference on 3D Web Technology, Pisa, Italy, November 8, 2021

Disentanglement and Local Directions of Variance.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Multimodal Self-supervised Learning for Medical Image Analysis.
Proceedings of the Information Processing in Medical Imaging, 2021

2020
Generative multi-adversarial network for striking the right balance in abdominal image segmentation.
Int. J. Comput. Assist. Radiol. Surg., 2020

3D Self-Supervised Methods for Medical Imaging.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generative synthetic adversarial network for internal bias correction and handling class imbalance problem in medical image diagnosis.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Two-sample Testing Using Deep Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018
Ensembles of Lasso Screening Rules.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Integrating omics and MRI data with kernel-based tests and CNNs to identify rare genetic markers for Alzheimer's disease.
CoRR, 2018

2017
Sparse probit linear mixed model.
Mach. Learn., 2017

2016
Separating Sparse Signals from Correlated Noise in Binary Classification.
Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

2015
Computational and statistical issues in personalized medicine.
XRDS, 2015

Sparse Estimation in a Correlated Probit Model.
CoRR, 2015

2014
Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.
Bioinform., 2014

2013
A Lasso multi-marker mixed model for association mapping with population structure correction.
Bioinform., 2013

A powerful and efficient set test for genetic markers that handles confounders.
Bioinform., 2013

Detecting regulatory gene-environment interactions with unmeasured environmental factors.
Bioinform., 2013

It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
easyGWAS: An integrated interspecies platform for performing genome-wide association studies
CoRR, 2012

2011
Efficient inference in matrix-variate Gaussian models with \iid observation noise.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Gene function prediction from synthetic lethality networks via ranking on demand.
Bioinform., 2010

2009
A kernel method for unsupervised structured network inference.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009


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