Bernhard Schölkopf - Citas de Google Académico

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Alex SmolaAmazon Web ServicesDirección de correo verificada de smola.org
John C. PlattGoogleDirección de correo verificada de google.com
Gunnar RätschProfessor, ETH ZürichDirección de correo verificada de inf.ethz.ch
Klaus-Robert MüllerProfessor for Machine Learning, TU Berlin, Germany and Korea University, Seoul, Korea and MPIIDirección de correo verificada de tu-berlin.de
arthur grettonGatsby Computational Neuroscience Unit, UCLDirección de correo verificada de gatsby.ucl.ac.uk
Dominik JanzingAmazon Development Center, TuebingenDirección de correo verificada de tuebingen.mpg.de
Jason WestonFacebookDirección de correo verificada de fb.com
Sebastian MikacomtravoDirección de correo verificada de comtravo.com
Olivier ChapelleGoogleDirección de correo verificada de chapelle.cc
Robert C. WilliamsonProfessor of Computer Science, Australian National University; Distinguished Researcher, DATA61Dirección de correo verificada de anu.edu.au
Koji TsudaProfessor, GSFS, The University of TokyoDirección de correo verificada de k.u-tokyo.ac.jp
Olivier BousquetGoogleDirección de correo verificada de m4x.org
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Moritz Grosse-WentrupUniversity of ViennaDirección de correo verificada de ieee.org
Jeremy HillResearch Scientist, Burke Neurological Institute and Blythedale Children's HospitalDirección de correo verificada de med.cornell.edu
Michael HirschMax Planck Institute for Intelligent Systems TübingenDirección de correo verificada de tuebingen.mpg.de
Jonas PetersProfessor of Statistics, University of CopenhagenDirección de correo verificada de math.ku.dk
vapnikProfessor of Columbia, Fellow of NEC Labs America, Dirección de correo verificada de nec-labs.com
Kun ZhangCarnegie Mellon University & Max-Planck Institute for Intelligent SystemsDirección de correo verificada de cmu.edu
Karsten BorgwardtProfessor of Machine Learning in the Life Sciences at ETH ZurichDirección de correo verificada de bsse.ethz.ch

Bernhard Schölkopf

Director, Max Planck Institute for Intelligent Systems; and Distinguished Amazon Scholar

Dirección de correo verificada de tuebingen.mpg.de

Machine Learning Causal Inference Artificial Intelligence Computational Photography Statistics


Título	Citado por	Año
11 label propagation and quadratic criterion Y Bengio, O Delalleau, N Le Roux	278	2006
3D reconstruction of neural circuits from serial EM images N Maack, C Kapfer, JH Macke, B Schölkopf, W Denk, A Borst 31st Göttingen Neurobiology Conference, 2007	2	2007
4th International BCI Meeting, May 31-June 4, 2010. Asilomar, CA, USA MG Rodriguez, M Grosse-Wentrup, J Hill, J Peters, B Schölkopf, ...
A 32‐channel multi‐coil setup optimized for human brain shimming at 9.4 T A Aghaeifar, J Zhou, R Heule, B Tabibian, B Schölkopf, F Jia, M Zaitsev, ... Magnetic resonance in medicine, 2019	2	2019
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time B Schölkopf, J Platt, T Hofmann MIT Press, 2007		2007
A blind deconvolution approach for improving the resolution of cryo-EM density maps M Hirsch, B Schölkopf, M Habeck Journal of Computational Biology 18 (3), 335-346, 2011	8	2011
A blind deconvolution approach for pseudo CT prediction from MR image pairs M Hirsch, M Hofmann, F Mantlik, BJ Pichler, B Schölkopf, M Habeck 2012 19th IEEE International Conference on Image Processing, 2953-2956, 2012	1	2012
A brain computer interface with online feedback based on magnetoencephalography TN Lal, M Schröder, NJ Hill, H Preissl, T Hinterberger, J Mellinger, ... Proceedings of the 22nd international conference on Machine learning, 465-472, 2005	76	2005
A brain-robot interface for studying motor learning after stroke T Meyer, J Peters, D Brötz, TO Zander, B Schölkopf, SR Soekadar, ... 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012	20	2012
A brain–computer interface based on self-regulation of gamma-oscillations in the superior parietal cortex M Grosse-Wentrup, B Schölkopf Journal of neural engineering 11 (5), 056015, 2014	29	2014
A Causal Perspective on Domain Adaptation M Rojas-Carulla, B Schölkopf, R Turner, J Peters stat 1050, 19, 2015		2015
A causal, data-driven approach to modeling the Kepler data D Wang, DW Hogg, D Foreman-Mackey, B Schölkopf Publications of the Astronomical Society of the Pacific 128 (967), 094503, 2016	8*	2016
A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis MR Hohmann, T Fomina, V Jayaram, N Widmann, C Förster, J Just, ... Progress in brain research 228, 221-239, 2016	8	2016
A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation YW Teh, D Newman, M Welling Advances in neural information processing systems, 1353-1360, 2007	592	2007
A combined corner and edge detector. JG Lv, WZ Kong, DY Li, W Kienzle, B Scholkopf, FA Wichmann, MO Franz, ... Journal of Software Engineering 9 (2), pp: 405-414, 2007		2007
A comparison of methods for multi-class support vector machines. A Mueen, MS Baba, R Zainuddin, T Acharya, K Ray, J Canny, C Carson, ... Journal of Applied Sciences 7 (8), 679-698, 2005		2005
A Complexity-Distortion Approach to Joint Pattern Alignment B Schölkopf, J Platt, T Hofmann MIT Press, 2007		2007
A compression approach to support vector model selection UV Luxburg, O Bousquet, B Schölkopf Journal of Machine Learning Research 5 (Apr), 293-323, 2004	72	2004
A direct method for building sparse kernel learning algorithms M Wu, B Schölkopf, G Bakır Journal of Machine Learning Research 7 (Apr), 603-624, 2006	121	2006
A discussion of semi-supervised learning and transduction O Chapelle, B Schölkopf, A Zien Semi-Supervised Learning, 457-462, 0	5

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