Publications of S Harmeling

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research 122, pp. 105 - 123 (2016)

Kitching, T.; Amara, A.; Gill, M.; Harmeling, S.; Heymans, C.; Massey, R.; Rowe, B.; Schrabback, T.; Voigt, L.; Balan, S. et al.; Bernstein, G.; Bethge, M.; Bridle, S.; Courbin, F.; Gentile, M.; Heavens, A.; Hirsch, M.; Hosseini, R.; Kiessling, A.; Kirk, D.; Kuijken, K.; Mandelbaum, R.; Moghaddam, B.; Nurbaeva, G.; Paulin-Henriksson , S.; Rassat, A.; Rhodes, J.; Schölkopf, B.; Shawe-Taylor, J.; Shmakova , M.; Taylor, A.; Velander, M.; van Waerbeke, L.; Witherick, D.; Wittman, D.: Gravitational Lensing Accuracy Testing 2010 (GREAT10) Challenge Handbook. Annals of Applied Statistics 5 (3), pp. 2231 - 2263 (2011)

Harmeling, S.; Williams , C.: Greedy Learning of Binary Latent Trees. IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (6), pp. 1087 - 1097 (2011)

Bridle, S.; Balan, S.; Bethge, M.; Gentile, M.; Harmeling, S.; Heymans, C.; Hirsch, M.; Hosseini, R.; Jarvis, M.; Kirk, D. et al.; Kitching, T.; Kuijken, K.; Lewis, A.; Paulin-Henriksson, S.; Schölkopf, B.; Velander, M.; Voigt, L.; Witherick, D.; Amara, A.; Bernstein, G.; Courbin, F.; Gill, M.; Heavens, A.; Mandelbaum, R.; Massey, R.; Moghaddam, B.; Rassat, A.; Refregier, A.; Rhodes, J.; Schrabback, T.; Shaw-Taylor, J.; Shmakova, M.; van Waerbeke, L.; Wittman, D.: Results of the GREAT08 Challenge: An image analysis competition for cosmological lensing. Monthly Notices of the Royal Astronomical Society 405 (3), pp. 2044 - 2061 (2010)

Baehrens, D.; Schroeter, T.; Harmeling, S.; Kawanabe, M.; Hansen, K.; Müller, K.-R.: How to Explain Individual Classification Decisions. Journal of Machine Learning Research 11, pp. 1803 - 1831 (2010)

Harmeling, S.: Inferring textual entailment with a probabilistically sound calculus. Natural Language Engineering 15 (4), pp. 459 - 477 (2009)

Köhler, R.; Hirsch, M.; Mohler, B.; Schölkopf, B.; Harmeling, S.: Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. In: Computer Vision - ECCV 2012, pp. 27 - 40 (Eds. Fitzgibbon, A.; Lazebnik, S.; Perona, P.; Sato, Y.; Schmid, C.). 12th European Conference on Computer Vision (ECCV 2012), Firenze, Italy, October 07, 2012 - October 13, 2012. Springer, Berlin, Germany (2012)

Loktyushin, A.; Harmeling, S.: Automatic foreground-background refocusing. In: 18th IEEE International Conference on Image Processing (ICIP 2011), pp. 3445 - 3448 (Eds. Macq, P.; Schelkens, B.). 18th IEEE International Conference on Image Processing (ICIP 2011), Brussels, Belgium. IEEE, Piscataway, NJ, USA (2011)

Harmeling, S.; Hirsch, M.; Schölkopf, B.: Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake. Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Vancouver, BC, Canada, December 06, 2010 - December 11, 2010. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, pp. 829 - 837 (2011)

Burger, H.; Schölkopf, B.; Harmeling, S.: Removing noise from astronomical images using a pixel-specific noise model. In: IEEE International Conference on Computational Photography (ICCP 2011), pp. 1 - 8 (Eds. Lensch, H.; Narasimhan, S.; Testorf, M.). IEEE International Conference on Computational Photography (ICCP 2011), Pittsburgh, PA, USA, April 08, 2011 - April 10, 2011. IEEE, Piscataway, NJ, USA (2011)

Harmeling, S.; Sra, S.; Hirsch, M.; Schölkopf, B.: Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM. In: 17th International Conference on Image Processing (ICIP 2010), pp. 3313 - 3316. 17th International Conference on Image Processing (ICIP 2010), Hong Kong, China, September 26, 2010 - September 29, 2010. IEEE, Piscataway, NJ, USA (2010)

Hirsch, M.; Sra, S.; Schölkopf, B.; Harmeling, S.: Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution. In: Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), pp. 607 - 614. Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13, 2010 - June 18, 2010. IEEE, Piscataway, NJ, USA (2010)

Lampert, C.; Nickisch, H.; Harmeling, S.: Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 951 - 958. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), Miami Beach, FL, USA, June 20, 2009 - June 25, 2009. IEEE Service Center, Piscataway, NJ, USA (2009)

Harmeling, S.; Hirsch, M.; Sra, S.; Schölkopf, B.: Online blind deconvolution for astronomical imaging. In: 2009 IEEE International Conference on Computational Photography (ICCP), pp. 1 - 7. First IEEE International Conference Computational Photography (ICCP 2009), San Francisco, CA, USA, April 16, 2009 - April 17, 2009. IEEE, Piscataway, NJ, USA (2009)

Harmeling, S.; Janzing, D.; Schölkopf, B.: Causal inference and identifying confounder with second order statistics. In Dagstuhl Reports, 09401, p. 6 (Eds. Janzing, D.; Lauritzen, B.; Schölkopf, B.). Dagstuhl Seminar: Machine learning approaches to statistical dependences and causality, Schloss Dagstuhl, Germany, September 27, 2009 - October 02, 2009. Schloss Dagstuhl, Leibniz-Zentrum für Informatik, Wadern (2009)

Harmeling, S.: Efficient space-variant blind deconvolution. NIPS 2010 Workshop on Numerical Mathematics Challenges in Machine Learning (NUMML 2010), Whistler, BC, Canada (2010)

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Psignifit 4: Pain-free Bayesian Inference for Psychometric Functions. 15th Annual Meeting of the Vision Sciences Society (VSS 2015), St. Pete Beach, FL, USA (2015)

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Pain-free bayesian inference for psychometric functions. 37th European Conference on Visual Perception (ECVP 2014), Beograd, Serbia (2014)

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.; Wichmann, F. A.: Pain-free Bayesian inference for psychometric functions. 2014 European Mathematical Psychology Group Meeting (EMPG), Tübingen, Germany (2014)

Harmeling, S.; Sra, S.; Hirsch, M.; Schölkopf, B.: An Incremental GEM Framework for Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction (Technical Report of the Max Planck Institute for Biological Cybernetics, 187). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2009), 9 pp.