Florian Steinke

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Matthias HofmannMax Planck Institut für biologische KybernetikVerified email at robots.ox.ac.uk
Thomas HamacherTechnische Universität MünchenVerified email at tum.de
Katrin SchaberHochschule BiberachVerified email at hochschule-bc.de
Matthias HeinProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
Philipp WolfrumResearch Scientist, Siemens Corporate TechnologyVerified email at siemens.com
Koji TsudaProfessor, GSFS, The University of TokyoVerified email at k.u-tokyo.ac.jp
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Guillaume CharpiatINRIA (Saclay)Verified email at inria.fr
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGVerified email at dbs.ifi.lmu.de
Volker BlanzProfessor of Computer Science, Universitaet SiegenVerified email at informatik.uni-siegen.de
Ilja BezrukovMax-Planck-Institute for Developmental BiologyVerified email at tuebingen.mpg.de
Tim JankeEnergy Information Networks & Systems @ TU DarmstadtVerified email at eins.tu-darmstadt.de
Kim, Kwang InGraduate School of Artificial Intelligence & Dept. Computer Science and Engineering, UNISTVerified email at unist.ac.kr
Emanuele Della VallePolitecnico di MilanoVerified email at polimi.it
Joshua L. MoorePhD Student, Cornell UniversityVerified email at cs.cornell.edu
Yasemin AltunGoogle ResearchVerified email at google.com
Nathan CahillRochester Institute of TechnologyVerified email at rit.edu
Irene CelinoHead of Knowledge Technologies group at CefrielVerified email at cefriel.com
Daniele Dell'AglioAssistant professor at Aalborg UniversityVerified email at cs.aau.dk

Florian Steinke

Professor, Energy Information Networks & Systems, TU Darmstadt

Verified email at eins.tu-darmstadt.de - Homepage

power systems smart grid machine learning optimization resilience


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MRI-based attenuation correction for PET/MRI: a novel approach combining pattern recognition and atlas registration M Hofmann, F Steinke, V Scheel, G Charpiat, J Farquhar, P Aschoff, ... Journal of nuclear medicine 49 (11), 1875-1883, 2008	537	2008
Bayesian inference and optimal design in the sparse linear model M Seeger, F Steinke, K Tsuda Artificial Intelligence and Statistics, 444-451, 2007	358	2007
Grid vs. storage in a 100% renewable Europe F Steinke, P Wolfrum, C Hoffmann Renewable Energy 50, 826-832, 2013	336	2013
MRI-based attenuation correction for whole-body PET/MRI: quantitative evaluation of segmentation-and atlas-based methods M Hofmann, I Bezrukov, F Mantlik, P Aschoff, F Steinke, T Beyer, ... Journal of Nuclear Medicine 52 (9), 1392-1399, 2011	295	2011
Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where? K Schaber, F Steinke, T Hamacher Energy Policy 43, 123-135, 2012	294	2012
Parametric study of variable renewable energy integration in Europe: Advantages and costs of transmission grid extensions K Schaber, F Steinke, P Mühlich, T Hamacher Energy policy 42, 498-508, 2012	177	2012
Semi-supervised regression using Hessian energy with an application to semi-supervised dimensionality reduction KI Kim, F Steinke, M Hein MPI for Biological Cybernetics, 2010	108	2010
Support vector machines for 3D shape processing F Steinke, B Schölkopf, V Blanz Computer Graphics Forum 24 (3), 285-294, 2005	101	2005
Learning similarity measure for multi-modal 3D image registration D Lee, M Hofmann, F Steinke, Y Altun, ND Cahill, B Scholkopf 2009 IEEE Conference on Computer Vision and Pattern Recognition, 186-193, 2009	85	2009
Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models F Steinke, M Seeger, K Tsuda BMC systems biology 1 (1), 1-15, 2007	65	2007
Managing temporary oversupply from renewables efficiently: Electricity storage versus energy sector coupling in germany K Schaber, F Steinke, T Hamacher International Energy Workshop, Paris, 2013	52	2013
Kernels, regularization and differential equations F Steinke, B Schölkopf Pattern Recognition 41 (11), 3271-3286, 2008	49	2008
Nonparametric regression between general Riemannian manifolds F Steinke, M Hein, B Schölkopf SIAM Journal on Imaging Sciences 3 (3), 527-563, 2010	46	2010
Non-parametric regression between manifolds F Steinke, M Hein Advances in Neural Information Processing Systems, 1561-1568, 2009	46	2009
Object correspondence as a machine learning problem B Schölkopf, F Steinke, V Blanz Proceedings of the 22nd international conference on Machine learning, 776-783, 2005	39	2005
The energy system development plan (ESDP) S Raths, S Koopmann, C Müller, A Meinerzhagen, T Falke, M Cramer, ... International ETG Congress 2015; Die Energiewende-Blueprints for the new …, 2015	25	2015
Learning dense 3d correspondence F Steinke, V Blanz, B Schölkopf Advances in Neural Information Processing Systems, 1313-1320, 2007	23	2007
Semantic traffic-aware routing using the larkc platform E Della Valle, I Celino, D Dell'Aglio, R Grothmann, F Steinke, V Tresp IEEE Internet Computing 15 (6), 15-23, 2011	21	2011
A novel metric for information retrieval in semantic networks JL Moore, F Steinke, V Tresp Extended Semantic Web Conference, 65-79, 2011	21	2011
Forecasting the price distribution of continuous intraday electricity trading T Janke, F Steinke Energies 12 (22), 4262, 2019	20	2019

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