Kernel Feature Spaces and Nonlinear Blind Souce Separation. - Stefan Harmeling; Andreas Ziehe; Motoaki Kawanabe; Klaus-Robert Müller (NIPS, 2001)

Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation. - Andreas Ziehe; Motoaki Kawanabe; Stefan Harmeling; Klaus-Robert Müller (J. Mach. Learn. Res., 2003)

Kernel-Based Nonlinear Blind Source Separation. - Stefan Harmeling; Andreas Ziehe; Motoaki Kawanabe; Klaus-Robert Müller (Neural Comput., 2003)

Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method. - Antti Honkela; Stefan Harmeling; Leo Lundqvist; Harri Valpola (ICA, 2004)

Robust ICA for Super-Gaussian Sources. - Frank C. Meinecke; Stefan Harmeling; Klaus-Robert Müller (ICA, 2004)

Injecting noise for analysing the stability of ICA components. - Stefan Harmeling; Frank C. Meinecke; Klaus-Robert Müller (Signal Process., 2004)

Independent component analysis and beyond. - Erkki Oja; Stefan Harmeling; Luís B. Almeida (Signal Process., 2004)

Inlier-based ICA with an application to superimposed images. - Frank C. Meinecke; Stefan Harmeling; Klaus-Robert Müller (Int. J. Imaging Syst. Technol., 2005)

Independent component analysis and beyond - Stefan Harmeling (2005)

From outliers to prototypes: Ordering data. - Stefan Harmeling; Guido Dornhege; David M. J. Tax; Frank C. Meinecke; Klaus-Robert Müller (Neurocomputing, 2006)

An Extensible Probabilistic Transformation-based Approach to the Third Recognizing Textual Entailment Challenge. - Stefan Harmeling (ACL-PASCAL@ACL, 2007)

Learning to detect unseen object classes by between-class attribute transfer. - Christoph H. Lampert; Hannes Nickisch; Stefan Harmeling (CVPR, 2009)

Inferring textual entailment with a probabilistically sound calculus. - Stefan Harmeling (Nat. Lang. Eng., 2009)

Efficient filter flow for space-variant multiframe blind deconvolution. - Michael Hirsch 001; Suvrit Sra; Bernhard Schölkopf; Stefan Harmeling (CVPR, 2010)

Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. - Stefan Harmeling; Suvrit Sra; Michael Hirsch 001; Bernhard Schölkopf (ICIP, 2010)

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. - Stefan Harmeling; Michael Hirsch 001; Bernhard Schölkopf (NIPS, 2010)

How to Explain Individual Classification Decisions. - David Baehrens; Timon Schroeter; Stefan Harmeling; Motoaki Kawanabe; Katja Hansen; Klaus-Robert Müller (J. Mach. Learn. Res., 2010)

Improving Denoising Algorithms via a Multi-scale Meta-procedure. - Harold Christopher Burger; Stefan Harmeling (DAGM-Symposium, 2011)

Removing noise from astronomical images using a pixel-specific noise model. - Harold Christopher Burger; Bernhard Schölkopf; Stefan Harmeling (ICCP, 2011)

Fast removal of non-uniform camera shake. - Michael Hirsch 001; Christian J. Schuler; Stefan Harmeling; Bernhard Schölkopf (ICCV, 2011)

Non-stationary correction of optical aberrations. - Christian J. Schuler; Michael Hirsch 001; Stefan Harmeling; Bernhard Schölkopf (ICCV, 2011)

Automatic foreground-background refocusing. - Alexander Loktyushin; Stefan Harmeling (ICIP, 2011)

Greedy Learning of Binary Latent Trees. - Stefan Harmeling; Christopher K. I. Williams (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Image denoising: Can plain neural networks compete with BM3D? - Harold Christopher Burger; Christian J. Schuler; Stefan Harmeling (CVPR, 2012)

Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. - Rolf Köhler; Michael Hirsch 001; Betty J. Mohler; Bernhard Schölkopf; Stefan Harmeling (ECCV (7), 2012)

Blind Correction of Optical Aberrations. - Christian J. Schuler; Michael Hirsch 001; Stefan Harmeling; Bernhard Schölkopf (ECCV (3), 2012)

Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds - Harold Christopher Burger; Christian J. Schuler; Stefan Harmeling (CoRR, 2012)

Image denoising with multi-layer perceptrons, part 2: training trade-offs and analysis of their mechanisms - Harold Christopher Burger; Christian J. Schuler; Stefan Harmeling (CoRR, 2012)

Climate Classifications: the Value of Unsupervised Clustering. - Jakob Zscheischler; Miguel D. Mahecha; Stefan Harmeling (ICCS, 2012)

On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit. - Stefan Harmeling; Michael Hirsch 001; Bernhard Schölkopf (CVPR, 2013)

A Machine Learning Approach for Non-blind Image Deconvolution. - Christian J. Schuler; Harold Christopher Burger; Stefan Harmeling; Bernhard Schölkopf (CVPR, 2013)

Learning How to Combine Internal and External Denoising Methods. - Harold Christopher Burger; Christian J. Schuler; Stefan Harmeling (GCPR, 2013)

Improving alpha matting and motion blurred foreground estimation. - Rolf Köhler; Michael Hirsch 001; Bernhard Schölkopf; Stefan Harmeling (ICIP, 2013)

How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data. - Moritz Grosse-Wentrup; Stefan Harmeling; Thorsten O. Zander; N. Jeremy Hill; Bernhard Schölkopf (PRNI, 2013)

Detection and attribution of large spatiotemporal extreme events in Earth observation data. - Jakob Zscheischler; Miguel D. Mahecha; Stefan Harmeling; Markus Reichstein (Ecol. Informatics, 2013)

Mask-Specific Inpainting with Deep Neural Networks. - Rolf Köhler; Christian J. Schuler; Bernhard Schölkopf; Stefan Harmeling (GCPR, 2014)

Attribute-Based Classification for Zero-Shot Visual Object Categorization. - Christoph H. Lampert; Hannes Nickisch; Stefan Harmeling (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Computing functions of random variables via reproducing kernel Hilbert space representations. - Bernhard Schölkopf; Krikamol Muandet; Kenji Fukumizu; Stefan Harmeling; Jonas Peters (Stat. Comput., 2015)

Learning to Deblur. - Christian J. Schuler; Michael Hirsch 001; Stefan Harmeling; Bernhard Schölkopf (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Parcellation of visual cortex on high-resolution histological brain sections using convolutional neural networks. - Hannah Spitzer; Katrin Amunts; Stefan Harmeling; Timo Dickscheid (ISBI, 2017)

Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks. - Hannah Spitzer; Kai Kiwitz; Katrin Amunts; Stefan Harmeling; Timo Dickscheid (MICCAI (3), 2018)

On the Vulnerability of Capsule Networks to Adversarial Attacks. - Felix Michels; Tobias Uelwer; Eric Upschulte; Stefan Harmeling (CoRR, 2019)

Modular Block-diagonal Curvature Approximations for Feedforward Architectures. - Felix Dangel; Stefan Harmeling; Philipp Hennig (AISTATS, 2020)

How Much Do I Argue Like You? Towards a Metric on Weighted Argumentation Graphs. - Markus Brenneis; Maike Behrendt; Stefan Harmeling; Martin Mauve (SAFA@COMMA, 2020)

Fast Multi-Level Foreground Estimation. - Thomas Germer; Tobias Uelwer; Stefan Conrad 001; Stefan Harmeling (ICPR, 2020)

Phase Retrieval Using Conditional Generative Adversarial Networks. - Tobias Uelwer; Alexander Oberstraß; Stefan Harmeling (ICPR, 2020)

Discrete Latent Space World Models for Reinforcement Learning. - Jan Robine; Tobias Uelwer; Stefan Harmeling (CoRR, 2020)

PyMatting: A Python Library for Alpha Matting. - Thomas Germer; Tobias Uelwer; Stefan Conrad 001; Stefan Harmeling (J. Open Source Softw., 2020)

Non-iterative Phase Retrieval with Cascaded Neural Networks. - Tobias Uelwer; Tobias Hoffmann; Stefan Harmeling (ICANN (2), 2021)

Learning to Plan via a Multi-step Policy Regression Method. - Stefan Wagner 020; Michael Janschek; Tobias Uelwer; Stefan Harmeling (ICANN (4), 2021)

Contrastive Representation Learning For Whole Brain Cytoarchitectonic Mapping In Histological Human Brain Sections. - Christian Schiffer; Katrin Amunts; Stefan Harmeling; Timo Dickscheid (ISBI, 2021)

2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks. - Christian Schiffer; Stefan Harmeling; Katrin Amunts; Timo Dickscheid (MICCAI (8), 2021)

How Will I Argue? A Dataset for Evaluating Recommender Systems for Argumentations. - Markus Brenneis; Maike Behrendt; Stefan Harmeling (SIGDIAL, 2021)

A Closer Look at Reference Learning for Fourier Phase Retrieval. - Tobias Uelwer; Nick Rucks; Stefan Harmeling (CoRR, 2021)

Convolutional neural networks for cytoarchitectonic brain mapping at large scale. - Christian Schiffer; Hannah Spitzer; Kai Kiwitz; Nina Unger; Konrad Wagstyl; Alan C. Evans; Stefan Harmeling; Katrin Amunts; Timo Dickscheid (NeuroImage, 2021)

Learning Causal Graphs in Manufacturing Domains using Structural Equation Models. - Maximilian Kertel; Stefan Harmeling; Markus Pauly (AI4I, 2022)

Uncertainty-Aware Contour Proposal Networks for Cell Segmentation in Multi-Modality High-Resolution Microscopy Images. - Eric Upschulte; Stefan Harmeling; Katrin Amunts; Timo Dickscheid (Cell Segmentation Challenge @ NeurIPS, 2022)

Deblurring Photographs of Characters Using Deep Neural Networks. - Thomas Germer; Tobias Uelwer; Stefan Harmeling (CoRR, 2022)

Blindly Deconvolving Super-noisy Blurry Image Sequences. - Leonid Kostrykin; Stefan Harmeling (CoRR, 2022)

Contour proposal networks for biomedical instance segmentation. - Eric Upschulte; Stefan Harmeling; Katrin Amunts; Timo Dickscheid (Medical Image Anal., 2022)

Optimizing Intermediate Representations of Generative Models for Phase Retrieval. - Tobias Uelwer; Sebastian Konietzny; Stefan Harmeling (Trans. Mach. Learn. Res., 2022)

Transformer-based World Models Are Happy With 100k Interactions. - Jan Robine; Marc Höftmann; Tobias Uelwer; Stefan Harmeling (ICLR, 2023)

Automatic Dictionary Generation: Could Brothers Grimm Create a Dictionary with BERT? - Hendryk Weiland; Maike Behrendt; Stefan Harmeling (KONVENS, 2023)

Time-Myopic Go-Explore: Learning A State Representation for the Go-Explore Paradigm. - Marc Höftmann; Jan Robine; Stefan Harmeling (CoRR, 2023)

A Survey on Self-Supervised Representation Learning. - Tobias Uelwer; Jan Robine; Stefan Sylvius Wagner; Marc Höftmann; Eric Upschulte; Sebastian Konietzny; Maike Behrendt; Stefan Harmeling (CoRR, 2023)

Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data. - Thomas Germer; Jan Robine; Sebastian Konietzny; Stefan Harmeling; Tobias Uelwer (CoRR, 2023)

Backward Learning for Goal-Conditioned Policies. - Marc Höftmann; Jan Robine; Stefan Harmeling (CoRR, 2023)

Learning Conditional Generative Models for Phase Retrieval. - Tobias Uelwer; Sebastian Konietzny; Alexander Oberstraß; Stefan Harmeling (J. Mach. Learn. Res., 2023)

Cyclophobic Reinforcement Learning. - Stefan Sylvius Wagner; Peter Arndt 001; Jan Robine; Stefan Harmeling (Trans. Mach. Learn. Res., 2023)

Learning Causal Graphs in Manufacturing Domains Using Structural Equation Models. - Maximilian Kertel; Stefan Harmeling; Markus Pauly; Nadja Klein (Int. J. Semantic Comput., 2023)

Smaller World Models for Reinforcement Learning. - Jan Robine; Tobias Uelwer; Stefan Harmeling (Neural Process. Lett., 2023)

Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations. - Stefan Sylvius Wagner; Stefan Harmeling (ICML, 2024)

AQuA - Combining Experts' and Non-Experts' Views To Assess Deliberation Quality in Online Discussions Using LLMs. - Maike Behrendt; Stefan Sylvius Wagner; Marc Ziegele; Lena Wilms; Anke Stoll; Dominique Heinbach; Stefan Harmeling (CoRR, 2024)

SQBC: Active Learning using LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions. - Stefan Sylvius Wagner; Maike Behrendt; Marc Ziegele; Stefan Harmeling (CoRR, 2024)

Supporting Online Discussions: Integrating AI Into the adhocracy+ Participation Platform To Enhance Deliberation. - Maike Behrendt; Stefan Sylvius Wagner; Stefan Harmeling (CoRR, 2024)

Simple, Good, Fast: Self-Supervised World Models Free of Baggage. - Jan Robine; Marc Höftmann; Stefan Harmeling (ICLR, 2025)

The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions. - Stefan Sylvius Wagner; Maike Behrendt; Marc Ziegele; Stefan Harmeling (ICLR, 2025)

Object-Aware DINO (Oh-A-Dino): Enhancing Self-Supervised Representations for Multi-Object Instance Retrieval. - Stefan Sylvius Wagner; Stefan Harmeling (CoRR, 2025)

A survey on self-supervised methods for visual representation learning. - Tobias Uelwer; Jan Robine; Stefan Sylvius Wagner; Marc Höftmann; Eric Upschulte; Sebastian Konietzny; Maike Behrendt; Stefan Harmeling (Mach. Learn., 2025)

MaxPoolBERT: Enhancing BERT Classification via Layer- and Token-Wise Aggregation. - Maike Behrendt; Stefan Sylvius Wagner; Stefan Harmeling (CoRR, 2025)

Natural Language Processing to Enhance Deliberation in Political Online Discussions: A Survey. - Maike Behrendt; Stefan Sylvius Wagner; Carina Weinmann; Marike Bormann; Mira Warne; Stefan Harmeling (CoRR, 2025)