See also the group's publication page.

Riemannian geometry for efficient analysis of protein dynamics data
Willem Diepeveen, Carlos Esteve-Yagüe, Jan Lellmann, Ozan Öktem, Carola-Bibiane Schönlieb, Proceedings of the National Academy of Sciences (PNAS), 2024.
pdf (preprint) | PNAS

Subtyping of rare types of gastric carcinomas and organoids for diagnostics using MALDI imaging
Pia Hönscheid, Linna Sommer, Patrick Moller Jensen, Jan Lellmann, Christian Sperling, Daniel Stange, Daniela Aust, Herbert Thiele, Gustavo Baretton, Conference on Mass Spectrometry Imaging and Integrated Topics (IMSIS), 2024.
(in preparation) | Poster at IMSIS 2024

Deep learning for MALDI-MSI: towards a common framework for transferable tissue diagnostics
Patrick M. Jensen, Jan Lellmann, Herbert Thiele, Pia Hönscheid, Christian Sperling, Gustavo Baretton, Oliver Klein, Carsten Tschöpe, Karin Klingel, 23rd Human Proteome World Congress (HUPO), 2024.
(in preparation) | Poster at HUPO 2024

A universal quantum algorithm for weighted maximum cut and Ising problems
Natacha Kuete Meli, Florian Mannel, Jan Lellmann, Quantum Information Processing, 2023
PDF (preprint) | SpringerLink

EmNeF: Neural Fields for Embedded Variational Problems in Imaging
Danielle Bednarski, Jan Lellmann, Scale Space Var. Meth. Comp. Vis. (SSVM) 2023.
SpringerLink

Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks
Frederic Kanter, Jan Lellmann, Herbert Thiele, Steve Kalloger, David F. Schaeffer, Axel Wellmann, Oliver Klein, Cancers, 2023.
web version | pdf (open access)

Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds
Willem Diepeveen, Jan Lellmann, Ozan Öktem, Carola-Bibiane Schönlieb, SIAM Journal on Imaging Sciences, 2023.
SIAM | pdf (preprint)

Inverse Scale Space Iterations for Non-Convex Variational Problems: The Continuous and Discrete Case
D. Bednarski, J. Lellmann, Journal of Mathematical Imaging and Vision, 2022.
SpringerLink | pdf (preprint)

On the Connection between Dynamical Optimal Transport and Functional Lifting
T. Vogt, R. Haase, D. Bednarski, J. Lellmann, Preprint, 2022
pdf (preprint)

A Flexible Meta Learning Model for Image Registration
F. Kanter, J. Lellmann, MIDL2022.
pdf (OpenReview)

An Iterative Quantum Approach for Transformation Estimation from Point Sets
N. Kuete-Meli, F. Mannel, J. Lellmann, CVPR2022.
pdf (CVF)

Deformable Groupwise Image Registration using Low-Rank and Sparse Decomposition
R. Haase, S. Heldmann, J. Lellmann, Journal of Mathematical Imaging and Vision, 2022.
SpringerLink | pdf (preprint)

An Inexact Semismooth Newton Method on Riemannian Manifolds with Application to Duality-Based Total Variation Denoising
W. Diepeveen, J. Lellmann, SIAM Journal on Imaging Sciences, 2021.
SIAM | pdf (preprint)
New: Our algorithm is now built into the open source manifold optimization package manopt.jl!

Inverse Scale Space Iterations for Non-Convex Variational Problems Using Functional Lifting
D. Bednarski, J. Lellmann, Best Student Paper Award at SSVM 2021.
SpringerLink | pdf (preprint)

Journal of Mathematical Imaging and Vision: Special Issue on Scale Space and Variational Methods in Computer Vision
J. Lellmann, J. Modersitzki (eds.)
SpringerLink (online first)

Higher-Order Total Directional Variation: Imaging Applications
S. Parisotto, J. Lellmann, S. Masnou, C.-B. Schönlieb, SIAM Journal on Imaging Sciences, 2020.
SIAM | pdf (preprint)

A multi-contrast MRI approach to thalamus segmentation
V. Corona, J. Lellmann, P. Nestor, C.-B. Schönlieb, J. Acosta-Cabronero, Human Brain Mapping, 2020.
Wiley Online

Lifting methods for manifold-valued variational problems
T. Vogt, E. Strekalovskiy, D. Cremers, J. Lellmann, Book chapter in Handbook of Variational Methods for Nonlinear Geometric Data, 2020.
SpringerLink | pdf (preprint)

Scale Space and Variational Methods in Computer Vision SSVM 2019, 7th International Conference, Proceedings
J. Lellmann, M. Burger, J. Modersitzki (Eds.), Springer Lecture Notes in Computer Science (LNCS), 2019.
SpringerLink

Functional Liftings of Vectorial Variational Problems with Laplacian Regularization
T. Vogt, J. Lellmann, Scale Space Var. Meth. Comp. Vis. (SSVM), 2019.
SpringerLink | pdf (preprint)

Measure-Valued Variational Models with Applications to Diffusion-Weighted Imaging
T. Vogt, J. Lellmann, Journal of Mathematical Imaging and Vision 2018.
Springer full text | SpringerLink | pdf (preprint)

A matrix-free approach to parallel and memory-efficient deformable image registration
Lars König, Jan Rühaak, Alexander Derksen, Jan Lellmann, SIAM Journal on Scientific Computing (SISC)
pdf (full text) | SIAM epubs | pdf (preprint)

MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods
Oliver Klein, Frederic Kanter, Hagen Kulbe, Paul Jank, Carsten Denkert, Grit Nebrich, Wolfgang D. Schmitt, Zhiyang Wu, Catarina A. Kunze, Jalid Sehouli, Silvia Darb-Esfahani, Ioana Braicu, Jan Lellmann, Herbert Thiele, Eliane T. Taube, Proteomics Clinical Applications, 2018.
Wiley (full text) | Wiley Online Library

Functional Lifting for Variational Problems with Higher-Order Regularization
B. Loewenhauser, J. Lellmann, IVLOPDE 2018 (online first).
SpringerLink

Fully-deformable 3D image registration in two seconds
Daniel Budelmann, Lars König, Nils Papenberg, Jan Lellmann, BVM 2019 (oral)
SpringerLink | pdf (preprint)

Image reconstruction with imperfect forward models and applications in deblurring
Y. Korolev, J. Lellmann, SIAM J. Imaging Sci. 11(1), 197-218, 2018
pdf (preprint) | SIAM epubs

An Optimal Transport-Based Restoration Method for Q-Ball Imaging
T. Vogt, J. Lellmann, Scale Space Var. Meth. Comp. Vis. (SSVM), 2017
pdf (preprint) | SpringerLink

Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies
E. Laude, T. Möllenhoff, M. Möller, J. Lellmann, D. Cremers. ECCV 2016.
pdf (preprint) | SpringerLink

Sublabel–Accurate Relaxation of Nonconvex Energies
T. Möllenhoff, E. Laude, M. Möller, J. Lellmann, D. Cremers.
Best Paper Honorable Mention at CVPR 2016.
pdf (preprint) | IEEE Xplore | Talk at CVPR'16 | Poster at CVPR'16 | Talk at SIAM IS'16

Individual Tree Species Classification From Airborne Multisensor Imagery Using Robust PCA
J. Lee, X. Cai, J. Lellmann, M. Dalponte, Y. Malhi, N. Butt, M. Morecroft, C.-B. Schönlieb, D. Coomes. J. Appl. Earth Obs. Remote Sensing, 2016. In Press.
pdf (preprint) | IEEE Xplore

A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems
J. H. Kappes, B. Andres, F. A. Hamprecht, C. Schnörr, S. Nowozin, D. Batra, S. Kim, B. X. Kausler, T. Kröger, J. Lellmann, N. Komodakis, B. Savchynskyy, and C. Rother, Int. J. Computer Vision, 2015.
pdf (preprint) | SpringerLink | Source code and benchmark data

Analysis and Application of a non-local Hessian
J. Lellmann, K. Papafitsoros, C. Schönlieb, D. Spector, SIAM J. Imaging Sci., 8(4), 2161–2202, 2015
pdf (preprint) | SpringerLink |Talk at SIAM Conference on Imaging Science 2014, Hong Kong | Poster at the RICAM Special Semester on New Trends in Calculus of Variations 2014, Linz

Imaging with Kantorovich-Rubinstein Discrepancy
J. Lellmann, D. A. Lorenz, C. Schönlieb, T. Valkonen, SIAM J. Imaging Sci., 7(4), 2833–2859, 2014
pdf (preprint) | SIAM epubs

Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets
F. Lenzen, J. Lellmann, F. Becker, and C. Schnörr, SIAM Journal on Imaging Science, 2014
SIAM epubs | pdf (preprint)

Total Variation Regularization for Functions with Values in a Manifold
J. Lellmann, E. Strekalovskiy, S. Koetter, and D. Cremers, to appear in: Int. Conf. Comp. Vis. (ICCV), 2013
pdf (preprint) | source code

Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
J. Lellmann, J.-M. Morel, and C. Schönlieb, Scale Space Var. Meth. Comp. Vis. (SSVM), 2013
pdf | Talk at SSVM 2013 | benchmark dataset

Adaptive Second-Order Total Variation: An Approach Aware of Surface Discontinuities
F. Lenzen, F. Becker, and J. Lellmann, Scale Space Var. Meth. Comp. Vis. (SSVM), 2013
pdf | Poster at SSVM 2013

Convex relaxations for a generalized Chan-Vese model
Egil Bae, Jan Lellmann, and Xue-Cheng Tai, Energy Min. Meth. Comp. Vis. Pattern Recogn. (EMMCVPR), 2013
pdf

A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems
J. H. Kappes, B. Andres, F. A. Hamprecht, C. Schnörr, S. Nowozin, D. Batra, S. Kim, B. X. Kausler, J. Lellmann, N. Komodakis, and C. Rother, Comp. Vis. Patt. Recogn. (CVPR) 2013.
IEEE Xplore | Source code and benchmark data

Discrete and Continuous Models for Partitioning Problems
J. Lellmann, B. Lellmann, F. Widmann, and C. Schnörr, International Journal of Computer Vision, 2013 (online first).
pdf | SpringerLink

Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
J. Lellmann, F. Lenzen, and C. Schnörr, Journal of Mathematical Imaging and Vision, 2012
pdf | SpringerLink | Talk at SIAM IS'12

A class of quasi-variational inequalities for adaptive image denoising and decomposition
F. Lenzen, F. Becker, J. Lellmann, S. Petra, and C. Schnörr, Comput. Optim. Appl., 2012
pdf | SpringerLink

COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis
D. Breitenreicher, J. Lellmann, and C. Schnörr, Optimization Methods and Software, 2012
Taylor & Francis

Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
J. Lellmann, F. Lenzen, and C. Schnörr, Energy Min. Meth. Comp. Vis. Patt. Recogn. (EMMCVPR), 2011
pdf | Talk at EMMCVPR'11 | Extended Technical Report (arXiv)

Variational Image Denoising with Adaptive Constraint Sets
F. Lenzen, F. Becker, and J. Lellmann, S. Petra, and C. Schnörr, Scale Space Var. Meth. Comp. Vis. (SSVM), 2011
pdf

Sparse Template-Based Variational Image Segmentation
D. Breitenreicher, J. Lellmann, and C. Schnörr, Advances in Adaptive Data Analysis, 2011
pdf | AADA

Continuous Multiclass Labeling Approaches and Algorithms
J. Lellmann and C. Schnörr, SIAM Journal on Imaging Sciences, 2011.
arXiv (revised technical report 2010) | HeiDOK (original technical report) | SIAM epubs

Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision
J. Lellmann, D. Breitenreicher, and C. Schnörr, Europ. Conf. Comp. Vis. (ECCV), 2010
pdf | SpringerLink | Poster at ECCV 2010 | Spotlight Slide

Convex Optimization for Multi-Class Image Labeling with a Novel Family of Total Variation Based Regularizers
J. Lellmann, F. Becker, and C. Schnörr, Int. Conf. Comp. Vis. (ICCV), 2009
pdf | IEEE Xplore | Poster at ICCV09

Convex Multi-Class Image Labeling by Simplex-Constrained Total Variation
J. Lellmann, J. Kappes, J. Yuan, F. Becker, and C. Schnörr, Scale Space Var. Meth. Comp. Vis. (SSVM), 2009
pdf | SpringerLink | Talk at SSVM'09 | Extended Tech. Rep. (Oct. 2008)

• Jan Lellmann: Nonsmooth Convex Variational Approaches to Image Analysis. University of Heidelberg, 2011 pdf

• J. Lellmann: A tour on lifting for image analysis and beyond Keynote at Helmholtz Imaging Conference, Hamburg, 2023.
• J. Lellmann: Dynamical Optimal Transport and Functional Lifting Invited talk at Mathematics and Image Analysis, Paris (virtual), 2021. pdf
• J. Lellmann: Higher-Order Non-Smooth Optimization on Manifolds Oberwolfach Mini-Workshop on Computational Optimization on Manifolds, 2020. pdf | Oberwolfach Report
• J. Lellmann: Measure-Valued Variational Image Processing Invited talk at IPAM Workshop on Geometric Processing as part of the long program “Geometry and Learning from Data in 3D and Beyond”, UCLA, Los Angles, 2019. pdf
• J. Lellmann: Manifolds & Relaxation Invited talk at CM2 Workshop on Manifold-Valued Image Processing, Kaiserslautern, 2016.
• J. Lellmann, E. Laude, T. Möllenhoff, D. Cremers, M. Möller, E. Strekalovskiy: Precise relaxation methods in image processing Invited talk at Imaging, Vision and Learning based on Optimization and PDEs (IVLOPDE), Bergen, 2016. pdf
• J. Lellmann, E. Laude, T. Möllenhoff, D. Cremers, M. Möller, E. Strekalovskiy: Precise Relaxation for Motion Estimation SIAM Conference on Imaging Science, Albuquerque, 2016. pdf
• F. Lenzen, J. Lellmann, F. Becker, S. Petra, J. Berger, C. Schnörr: Solution-driven Adaptive Total Variation Regularization SIAM Conference on Imaging Science, Albuquerque, 2016. pdf
• J. Lellmann, E. Laude, T. Moellenhoff, D. Cremers, M. Moeller, E. Strekalovskiy: Relaxation Methods in Variational Image Processing 37th Northern German Colloquium on Applied Analysis and Numerical Mathematics, Lübeck, 2016. pdf
• J. Lellmann: Visualizing Image Processing/imaging.live Joint Annual Meeting of GAMM/DMV, Braunschweig, 2016. Imaging Live project page
• R. Tovey, J. Lellmann: Asymmetric Regularization of Higher-Order Derivatives. Joint Annual Meeting of GAMM/DMV, Braunschweig, 2016. pdf
• J. Lellmann: Encoding Prior Knowledge in Image- and Data Processing. 3rd Heidelberg Laureate Forum, Heidelberg, 2015.pdf
• J. Lellmann, D. A. Lorenz, C. Schönlieb, T. Valkonen: Imaging with Kantorovich-Rubinstein Discrepancy. ICMS Workshop on Gradient Flows: from theory to application, Edinburgh, 2015. pdf
• Jan Lellmann: Variational problems with finite and infinite label spaces. 4th Joint British Mathematical Colloquium & British Applied Mathematics Colloquium, Cambridge, 2015 pdf
• Jan Lellmann: Variational models with finite and infinite label spaces. Invited Talk at the Minerva Weizmann Workshop on Computational Challenges in Large Scale Image Analysis, Rehovot, 2015 pdf
• Jan Lellmann, Carola-Bibiane Schönlieb: The blessing and the curse of the big image. Invited talk at the “The Vocabulary of Big Data” workshop as part of the Cambridge Big Data lecture series, Cambridge, 2015 pdf
• Jan Lellmann, Kostas Papafitsoros, Daniel Spector, Carola Schönlieb: A non-local formulation for higher-order total variation-based regularization. SIAM Conference on Imaging Science, Hong Kong, 2014 pdf
• Jan Lellmann: Convexity and Non-Convexity in Partitioning and Interpolation Problems. Invited Talk at IPAM Workshop on Convex Relaxation Methods for Geometric Problems in Scientific Computing, Los Angeles, 2013. pdf
• Jan Lellmann, Frank Lenzen, Christoph Schnörr: Optimality Bounds and Optimization for Image Partitioning. Talk at Workshop on Efficient Algorithms for Global Optimisation Methods, Dagstuhl, 2011. pdf
• Jan Lellmann: Fast Numerical Methods for Continuous Multiclass Labeling. Talk at 81st Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Karlsruhe, 2010. pdf
• Jan Lellmann, Christoph Schnörr: On Metric Image Labeling and Sparsity. Invited Talk at Int. Conf. on Sparse Representation of Multiscale Data and Images (SRMDI), Nanyang, 2009. pdf

• Jan Lellmann, Christoph Schnörr: Regularizers for Vector-Valued Data and Labeling Problems in Image Processing. Control Systems and Computers, 2:43-54, 2011. pdf
• Jan Lellmann, Jonathan Balzer, Andreas Rieder, Jürgen Beyerer: Shape from Specular Reflection and Optical Flow. Int. Journal of Computer Vision, Vol. 80 No. 2, November 2008. SpringerLink, preprint (IWRMM)
• Jan Albiez, Björn Giesler, Jan Lellmann, J. Marius Zöllner and Rüdiger Dillmann: Virtual Immersion for Tele-Controlling a Hexapod Robot. Industrial Robot Highly Commended Award at CLAWAR05. SpringerLink

• IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI)
• International Journal of Computer Vision (IJCV)
• SIAM Journal on Imaging Sciences (SIIMS)
• Journal of Mathematical Imaging and Vision (JMIV)
• European Conference on Computer Vision (ECCV)
• International Conference on Computer Vision (ICCV)
• SIAM Journal on Scientific Computing (JSciComp)
• Inverse problems (IP)
• AMS Mathematical Reviews
• Computational Mathematics
• Numerical Algorithms
• IMA Journal of Numerical Analysis
• Calcolo
• Scale Space and Variational Methods (SSVM)
• Medical Imaging with Deep Learning (MIDL)
• Österreichischer Wissenschaftsfonds (FWF)
• Deutsche Forschungsgemeinschaft (DFG)
• Nature Scientific Reports

• Minisymposium on Model- and Data-Driven Approaches in Motion Analysis, SIAM Conference on Imaging Science, Atlanta, 2024
• International Conference on Medical Imaging with Deep Learning (MIDL), Lübeck, 2021
• Seventh International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), Hofgeismar, 2019
• Minisymposium on Optimal transport and Applications in Image Analysis, SIAM Conference on Imaging Science, Toronto, 2020
• Minisymposium on Optimal Transport in Image and Shape Analysis, International Conference on Scientific Computation And Differential Equations (SciCADE), Potsdam, 2015
• Minisymposium on Tensor- and Manifold-Valued Data, SIAM Conference on Imaging Science, Hong Kong, 2014
• Workshop on Statistics, Learning and Variational Methods in Imaging at the University of Cambridge