default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStefan Harmeling
Person information
- affiliation: Technische Universität Dortmund, Dortmund, Germany
- affiliation (former): Heinrich Heine University of Düsseldorf, Computer Science Department, Germany
- affiliation (former): Max Planck Institute for Intelligent Systems, Tübinngen, Germany
- affiliation (former): Fraunhofer FIRST, Berlin, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c39]Stefan Sylvius Wagner, Stefan Harmeling:
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations. ICML 2024- [i33]Stefan Sylvius Wagner, Stefan Harmeling:
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations. CoRR abs/2402.03138 (2024) - [i32]Maike Behrendt, Stefan Sylvius Wagner, Marc Ziegele, Lena Wilms, Anke Stoll, Dominique Heinbach, Stefan Harmeling:
AQuA - Combining Experts' and Non-Experts' Views To Assess Deliberation Quality in Online Discussions Using LLMs. CoRR abs/2404.02761 (2024) - [i31]Stefan Sylvius Wagner, Maike Behrendt, Marc Ziegele, Stefan Harmeling:
SQBC: Active Learning using LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions. CoRR abs/2404.08078 (2024) - [i30]Stefan Sylvius Wagner, Maike Behrendt, Marc Ziegele, Stefan Harmeling:
The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions. CoRR abs/2406.12480 (2024) - [i29]Maike Behrendt, Stefan Sylvius Wagner, Stefan Harmeling:
Supporting Online Discussions: Integrating AI Into the adhocracy+ Participation Platform To Enhance Deliberation. CoRR abs/2409.07780 (2024) - 2023
- [j21]Maximilian Kertel
, Stefan Harmeling, Markus Pauly, Nadja Klein:
Learning Causal Graphs in Manufacturing Domains Using Structural Equation Models. Int. J. Semantic Comput. 17(4): 511-528 (2023) - [j20]Tobias Uelwer, Sebastian Konietzny, Alexander Oberstraß, Stefan Harmeling:
Learning Conditional Generative Models for Phase Retrieval. J. Mach. Learn. Res. 24: 332:1-332:28 (2023) - [j19]Jan Robine, Tobias Uelwer, Stefan Harmeling:
Smaller World Models for Reinforcement Learning. Neural Process. Lett. 55(8): 11397-11427 (2023) - [j18]Stefan Sylvius Wagner, Peter Arndt, Jan Robine, Stefan Harmeling:
Cyclophobic Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c38]Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling:
Transformer-based World Models Are Happy With 100k Interactions. ICLR 2023 - [c37]Hendryk Weiland, Maike Behrendt, Stefan Harmeling:
Automatic Dictionary Generation: Could Brothers Grimm Create a Dictionary with BERT? KONVENS 2023: 102-120 - [i28]Marc Höftmann, Jan Robine, Stefan Harmeling:
Time-Myopic Go-Explore: Learning A State Representation for the Go-Explore Paradigm. CoRR abs/2301.05635 (2023) - [i27]Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling:
Transformer-based World Models Are Happy With 100k Interactions. CoRR abs/2303.07109 (2023) - [i26]Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Marc Höftmann, Eric Upschulte, Sebastian Konietzny, Maike Behrendt, Stefan Harmeling:
A Survey on Self-Supervised Representation Learning. CoRR abs/2308.11455 (2023) - [i25]Stefan Sylvius Wagner, Peter Arndt, Jan Robine, Stefan Harmeling:
Cyclophobic Reinforcement Learning. CoRR abs/2308.15911 (2023) - [i24]Thomas Germer, Jan Robine, Sebastian Konietzny, Stefan Harmeling, Tobias Uelwer:
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data. CoRR abs/2309.06948 (2023) - [i23]Marc Höftmann, Jan Robine, Stefan Harmeling:
Backward Learning for Goal-Conditioned Policies. CoRR abs/2312.05044 (2023) - 2022
- [j17]Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
Contour proposal networks for biomedical instance segmentation. Medical Image Anal. 77: 102371 (2022) - [j16]Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling:
Optimizing Intermediate Representations of Generative Models for Phase Retrieval. Trans. Mach. Learn. Res. 2022 (2022) - [c36]Maximilian Kertel, Stefan Harmeling, Markus Pauly:
Learning Causal Graphs in Manufacturing Domains using Structural Equation Models. AI4I 2022: 14-19 - [c35]Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
Uncertainty-Aware Contour Proposal Networks for Cell Segmentation in Multi-Modality High-Resolution Microscopy Images. Cell Segmentation Challenge @ NeurIPS 2022: 1-12 - [i22]Thomas Germer, Tobias Uelwer, Stefan Harmeling:
Deblurring Photographs of Characters Using Deep Neural Networks. CoRR abs/2205.15053 (2022) - [i21]Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling:
Optimizing Intermediate Representations of Generative Models for Phase Retrieval. CoRR abs/2205.15617 (2022) - [i20]Leonid Kostrykin, Stefan Harmeling:
Blindly Deconvolving Super-noisy Blurry Image Sequences. CoRR abs/2210.00252 (2022) - [i19]Maximilian Kertel, Stefan Harmeling, Markus Pauly:
Learning Causal Graphs in Manufacturing Domains using Structural Equation Models. CoRR abs/2210.14573 (2022) - 2021
- [j15]Christian Schiffer, Hannah Spitzer, Kai Kiwitz, Nina Unger, Konrad Wagstyl, Alan C. Evans, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
Convolutional neural networks for cytoarchitectonic brain mapping at large scale. NeuroImage 240: 118327 (2021) - [c34]Tobias Uelwer, Tobias Hoffmann, Stefan Harmeling:
Non-iterative Phase Retrieval with Cascaded Neural Networks. ICANN (2) 2021: 295-306 - [c33]Stefan Wagner, Michael Janschek, Tobias Uelwer, Stefan Harmeling:
Learning to Plan via a Multi-step Policy Regression Method. ICANN (4) 2021: 481-492 - [c32]Christian Schiffer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Contrastive Representation Learning For Whole Brain Cytoarchitectonic Mapping In Histological Human Brain Sections. ISBI 2021: 603-606 - [c31]Christian Schiffer, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks. MICCAI (8) 2021: 395-404 - [c30]Markus Brenneis, Maike Behrendt, Stefan Harmeling:
How Will I Argue? A Dataset for Evaluating Recommender Systems for Argumentations. SIGDIAL 2021: 360-367 - [i18]Christian Schiffer, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks. CoRR abs/2103.05259 (2021) - [i17]Eric Upschulte, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
Contour Proposal Networks for Biomedical Instance Segmentation. CoRR abs/2104.03393 (2021) - [i16]Stefan Wagner, Michael Janschek, Tobias Uelwer, Stefan Harmeling:
Learning to Plan via a Multi-Step Policy Regression Method. CoRR abs/2106.10075 (2021) - [i15]Tobias Uelwer, Tobias Hoffmann, Stefan Harmeling:
Non-Iterative Phase Retrieval With Cascaded Neural Networks. CoRR abs/2106.10195 (2021) - [i14]Tobias Uelwer, Nick Rucks, Stefan Harmeling:
A Closer Look at Reference Learning for Fourier Phase Retrieval. CoRR abs/2110.13688 (2021) - 2020
- [j14]Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling:
PyMatting: A Python Library for Alpha Matting. J. Open Source Softw. 5(54): 2481 (2020) - [c29]Felix Dangel, Stefan Harmeling, Philipp Hennig:
Modular Block-diagonal Curvature Approximations for Feedforward Architectures. AISTATS 2020: 799-808 - [c28]Markus Brenneis, Maike Behrendt, Stefan Harmeling, Martin Mauve:
How Much Do I Argue Like You? Towards a Metric on Weighted Argumentation Graphs. SAFA@COMMA 2020: 2-13 - [c27]Tobias Uelwer, Alexander Oberstraß, Stefan Harmeling:
Phase Retrieval Using Conditional Generative Adversarial Networks. ICPR 2020: 731-738 - [c26]Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling:
Fast Multi-Level Foreground Estimation. ICPR 2020: 1104-1111 - [i13]Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling:
PyMatting: A Python Library for Alpha Matting. CoRR abs/2003.12382 (2020) - [i12]Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling:
Fast Multi-Level Foreground Estimation. CoRR abs/2006.14970 (2020) - [i11]Jan Robine, Tobias Uelwer, Stefan Harmeling:
Discrete Latent Space World Models for Reinforcement Learning. CoRR abs/2010.05767 (2020) - [i10]Christian Schiffer, Hannah Spitzer, Kai Kiwitz, Nina Unger, Konrad Wagstyl, Alan C. Evans, Stefan Harmeling, Katrin Amunts, Timo Dickscheid:
Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale. CoRR abs/2011.12857 (2020) - [i9]Christian Schiffer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Contrastive Representation Learning for Whole Brain Cytoarchitectonic Mapping in Histological Human Brain Sections. CoRR abs/2011.12865 (2020)
2010 – 2019
- 2019
- [i8]Felix Michels, Tobias Uelwer, Eric Upschulte, Stefan Harmeling:
On the Vulnerability of Capsule Networks to Adversarial Attacks. CoRR abs/1906.03612 (2019) - [i7]Tobias Uelwer, Alexander Oberstraß, Stefan Harmeling:
Phase Retrieval using Conditional Generative Adversarial Networks. CoRR abs/1912.04981 (2019) - 2018
- [c25]Hannah Spitzer, Kai Kiwitz, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks. MICCAI (3) 2018: 663-671 - [i6]Hannah Spitzer, Kai Kiwitz, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks. CoRR abs/1806.05104 (2018) - 2017
- [c24]Hannah Spitzer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Parcellation of visual cortex on high-resolution histological brain sections using convolutional neural networks. ISBI 2017: 920-923 - [i5]Hannah Spitzer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid:
Parcellation of Visual Cortex on high-resolution histological Brain Sections using Convolutional Neural Networks. CoRR abs/1705.10545 (2017) - 2016
- [j13]Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf:
Learning to Deblur. IEEE Trans. Pattern Anal. Mach. Intell. 38(7): 1439-1451 (2016) - 2015
- [j12]Bernhard Schölkopf, Krikamol Muandet, Kenji Fukumizu, Stefan Harmeling, Jonas Peters:
Computing functions of random variables via reproducing kernel Hilbert space representations. Stat. Comput. 25(4): 755-766 (2015) - 2014
- [j11]Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling:
Attribute-Based Classification for Zero-Shot Visual Object Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 453-465 (2014) - [c23]Rolf Köhler, Christian J. Schuler, Bernhard Schölkopf, Stefan Harmeling:
Mask-Specific Inpainting with Deep Neural Networks. GCPR 2014: 523-534 - [i4]Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf:
Learning to Deblur. CoRR abs/1406.7444 (2014) - 2013
- [j10]Jakob Zscheischler, Miguel D. Mahecha, Stefan Harmeling, Markus Reichstein:
Detection and attribution of large spatiotemporal extreme events in Earth observation data. Ecol. Informatics 15: 66-73 (2013) - [c22]Christian J. Schuler, Harold Christopher Burger, Stefan Harmeling, Bernhard Schölkopf:
A Machine Learning Approach for Non-blind Image Deconvolution. CVPR 2013: 1067-1074 - [c21]Stefan Harmeling, Michael Hirsch, Bernhard Schölkopf:
On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit. CVPR 2013: 1083-1090 - [c20]Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling:
Learning How to Combine Internal and External Denoising Methods. GCPR 2013: 121-130 - [c19]Rolf Köhler, Michael Hirsch, Bernhard Schölkopf, Stefan Harmeling:
Improving alpha matting and motion blurred foreground estimation. ICIP 2013: 3446-3450 - [c18]Moritz Grosse-Wentrup, Stefan Harmeling, Thorsten O. Zander, N. Jeremy Hill, Bernhard Schölkopf:
How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data. PRNI 2013: 102-105 - 2012
- [c17]Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling:
Image denoising: Can plain neural networks compete with BM3D? CVPR 2012: 2392-2399 - [c16]Rolf Köhler, Michael Hirsch, Betty J. Mohler, Bernhard Schölkopf, Stefan Harmeling:
Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. ECCV (7) 2012: 27-40 - [c15]Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf:
Blind Correction of Optical Aberrations. ECCV (3) 2012: 187-200 - [c14]Jakob Zscheischler, Miguel D. Mahecha, Stefan Harmeling:
Climate Classifications: the Value of Unsupervised Clustering. ICCS 2012: 897-906 - [i3]Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling:
Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds. CoRR abs/1211.1544 (2012) - [i2]Harold Christopher Burger, Christian J. Schuler, Stefan Harmeling:
Image denoising with multi-layer perceptrons, part 2: training trade-offs and analysis of their mechanisms. CoRR abs/1211.1552 (2012) - 2011
- [j9]Stefan Harmeling, Christopher K. I. Williams:
Greedy Learning of Binary Latent Trees. IEEE Trans. Pattern Anal. Mach. Intell. 33(6): 1087-1097 (2011) - [c13]Harold Christopher Burger, Stefan Harmeling:
Improving Denoising Algorithms via a Multi-scale Meta-procedure. DAGM-Symposium 2011: 206-215 - [c12]Harold Christopher Burger, Bernhard Schölkopf, Stefan Harmeling:
Removing noise from astronomical images using a pixel-specific noise model. ICCP 2011: 1-8 - [c11]Michael Hirsch, Christian J. Schuler, Stefan Harmeling, Bernhard Schölkopf:
Fast removal of non-uniform camera shake. ICCV 2011: 463-470 - [c10]Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf:
Non-stationary correction of optical aberrations. ICCV 2011: 659-666 - [c9]Alexander Loktyushin, Stefan Harmeling:
Automatic foreground-background refocusing. ICIP 2011: 3445-3448 - 2010
- [j8]David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller:
How to Explain Individual Classification Decisions. J. Mach. Learn. Res. 11: 1803-1831 (2010) - [c8]Michael Hirsch, Suvrit Sra, Bernhard Schölkopf, Stefan Harmeling:
Efficient filter flow for space-variant multiframe blind deconvolution. CVPR 2010: 607-614 - [c7]Stefan Harmeling, Suvrit Sra, Michael Hirsch, Bernhard Schölkopf:
Multiframe blind deconvolution, super-resolution, and saturation correction via incremental EM. ICIP 2010: 3313-3316 - [c6]Stefan Harmeling, Michael Hirsch, Bernhard Schölkopf:
Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. NIPS 2010: 829-837
2000 – 2009
- 2009
- [j7]Stefan Harmeling:
Inferring textual entailment with a probabilistically sound calculus. Nat. Lang. Eng. 15(4): 459-477 (2009) - [c5]Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling:
Learning to detect unseen object classes by between-class attribute transfer. CVPR 2009: 951-958 - [i1]David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller:
How to Explain Individual Classification Decisions. CoRR abs/0912.1128 (2009) - 2007
- [c4]Stefan Harmeling:
An Extensible Probabilistic Transformation-based Approach to the Third Recognizing Textual Entailment Challenge. ACL-PASCAL@ACL 2007: 137-142 - 2006
- [j6]Stefan Harmeling, Guido Dornhege, David M. J. Tax, Frank C. Meinecke, Klaus-Robert Müller:
From outliers to prototypes: Ordering data. Neurocomputing 69(13-15): 1608-1618 (2006) - 2005
- [b1]Stefan Harmeling:
Independent component analysis and beyond. University of Potsdam, Germany, 2005 - [j5]Frank C. Meinecke, Stefan Harmeling, Klaus-Robert Müller:
Inlier-based ICA with an application to superimposed images. Int. J. Imaging Syst. Technol. 15(1): 48-55 (2005) - 2004
- [j4]Erkki Oja, Stefan Harmeling, Luís B. Almeida:
Independent component analysis and beyond. Signal Process. 84(2): 215-216 (2004) - [j3]Stefan Harmeling, Frank C. Meinecke, Klaus-Robert Müller:
Injecting noise for analysing the stability of ICA components. Signal Process. 84(2): 255-266 (2004) - [c3]Frank C. Meinecke, Stefan Harmeling, Klaus-Robert Müller:
Robust ICA for Super-Gaussian Sources. ICA 2004: 217-224 - [c2]Antti Honkela, Stefan Harmeling, Leo Lundqvist, Harri Valpola:
Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method. ICA 2004: 790-797 - 2003
- [j2]Andreas Ziehe, Motoaki Kawanabe, Stefan Harmeling, Klaus-Robert Müller:
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation. J. Mach. Learn. Res. 4: 1319-1338 (2003) - [j1]Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller:
Kernel-Based Nonlinear Blind Source Separation. Neural Comput. 15(5): 1089-1124 (2003) - 2001
- [c1]Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller:
Kernel Feature Spaces and Nonlinear Blind Souce Separation. NIPS 2001: 761-768
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-14 23:25 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
