Harmeling, S., Hirsch, M., Sra, S., Schölkopf, B., Schuler, C.
Method and device for recovering a digital image from a sequence of observed digital images
European Patent, No. 11767924.1, November 2015 (patent)
Charpiat, G., Hofmann, M., Schölkopf, B.
Kernel methods in medical imaging
In Handbook of Biomedical Imaging, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)
O’Donnell, L. J., Schultz, T.
Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data
In Visualization and Processing of Higher Order Descriptors for Multi-Valued Data, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)
Janzing, D., Steudel, B., Shajarisales, N., Schölkopf, B.
Justifying Information-Geometric Causal Inference
In Measures of Complexity: Festschrift for Alexey Chervonenkis, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)
Schuler, C., Hirsch, M., Harmeling, S., Schölkopf, B.
Method and device for blind correction of optical aberrations in a digital image
International Patent Application, No. PCT/EP2012/068868, April 2014 (patent)
Zhang, K., Schölkopf, B., Muandet, K., Wang, Z., Zhou, Z., Persello, C.
Single-Source Domain Adaptation with Target and Conditional Shift
In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 427-456, 19, Chapman & Hall/CRC Machine Learning & Pattern Recognition, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), Chapman and Hall/CRC, Boca Raton, USA, 2014 (inbook)
Schultz, T., Fuster, A., Ghosh, A., Deriche, R., Florack, L., Lim, L.
Higher-Order Tensors in Diffusion Imaging
In Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, pages: 129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (inbook)
Schultz, T., Vilanova, A., Brecheisen, R., Kindlmann, G.
Fuzzy Fibers: Uncertainty in dMRI Tractography
In Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization, pages: 79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (inbook)
Sra, S.
Nonconvex Proximal Splitting with Computational Errors
In Regularization, Optimization, Kernels, and Support Vector Machines, pages: 83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (inbook)
Balcan, M., Urner, R.
Active Learning - Modern Learning Theory
In Encyclopedia of Algorithms, (Editors: Kao, M.-Y.), Springer Berlin Heidelberg, 2014 (incollection)
Schölkopf, B., Smola, A., Müller, K.
Kernel principal component analysis.
In Advances in Kernel Methods—Support Vector Learning, pages: 327-352, (Editors: B Schölkopf and CJC Burges and AJ Smola), MIT Press, Cambridge, MA, 1999 (inbook)
Williamson, R., Smola, A., Schölkopf, B.
Entropy numbers, operators and support vector kernels.
In Advances in Kernel Methods - Support Vector Learning, pages: 127-144, (Editors: B Schölkopf and CJC Burges and AJ Smola), MIT Press, Cambridge, MA, 1999 (inbook)