Matthias Seeger

Cited by

	All	Since 2020
Citations	18608	9314
h-index	44	35
i10-index	79	58

2200

1100

550

1650

20022003200420052006200720082009201020112012201320142015201620172018201920202021202220232024202594 113 188 250 254 304 320 407 462 554 549 562 691 694 818 771 873 1196 1417 1605 1818 1933 2124 410

Public access

View all

6 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Cédric ArchambeauDirector of AI at Helsing. Ex Principal Applied Scientist at AWS.Verified email at helsing.ai
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
Rodolphe JENATTONCTO at BioptimusVerified email at bioptimus.com
Hannes NickischPhilips ResearchVerified email at philips.com
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Aaron KleinScaDS.AIVerified email at amazon.com
David SalinasUniversity of FreiburgVerified email at ens-lyon.org
Ralf HerbrichHasso Plattner InstituteVerified email at hpi.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Andrew NgStanford UniversityVerified email at cs.stanford.edu
Florian SteinkeProfessor, Energy Information Networks & Systems, TU DarmstadtVerified email at eins.tu-darmstadt.de
Martin WistubaAmazon Web ServicesVerified email at ismll.de

Matthias Seeger

Principal Applied Scientist, Amazon, Berlin

Verified email at amazon.de - Homepage

Machine Learning Bayesian Statistics Bayesian Optimization


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Using the Nyström method to speed up kernel machines C Williams, M Seeger Advances in neural information processing systems 13, 2000	3179	2000
Gaussian process optimization in the bandit setting: No regret and experimental design N Srinivas, A Krause, SM Kakade, M Seeger arXiv preprint arXiv:0912.3995, 2009	2938	2009
Gaussian processes for machine learning M Seeger International journal of neural systems 14 (02), 69-106, 2004	1508	2004
Information-theoretic regret bounds for gaussian process optimization in the bandit setting N Srinivas, A Krause, SM Kakade, MW Seeger IEEE transactions on information theory 58 (5), 3250-3265, 2012	1105	2012
Deep state space models for time series forecasting SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ... Advances in neural information processing systems 31, 2018	913	2018
Fast sparse Gaussian process methods: The informative vector machine N Lawrence, M Seeger, R Herbrich Advances in neural information processing systems 15, 2002	759	2002
Learning with labeled and unlabeled data M Seeger	742	2000
Fast forward selection to speed up sparse Gaussian process regression MW Seeger, CKI Williams, ND Lawrence International Workshop on Artificial Intelligence and Statistics, 254-261, 2003	676	2003
PAC-Bayesian generalisation error bounds for Gaussian process classification M Seeger Journal of machine learning research 3 (Oct), 233-269, 2002	447	2002
Model learning with local gaussian process regression D Nguyen-Tuong, M Seeger, J Peters Advanced Robotics 23 (15), 2015-2034, 2009	414	2009
Bayesian inference and optimal design in the sparse linear model M Seeger, F Steinke, K Tsuda Artificial Intelligence and Statistics, 444-451, 2007	387	2007
Local Gaussian process regression for real time online model learning D Nguyen-Tuong, J Peters, M Seeger Advances in neural information processing systems 21, 2008	360	2008
Semiparametric latent factor models YW Teh, M Seeger, MI Jordan International Workshop on Artificial Intelligence and Statistics, 333-340, 2005	325	2005
Bayesian Gaussian process models: PAC-Bayesian generalisation error bounds and sparse approximations M Seeger University of Edinburgh, 2003	261	2003
Leep: A new measure to evaluate transferability of learned representations C Nguyen, T Hassner, M Seeger, C Archambeau International Conference on Machine Learning, 7294-7305, 2020	252	2020
The effect of the input density distribution on kernel-based classifiers C Williams, M Seeger Proceedings of the 17th international conference on machine learning, 1159-1166, 2000	244	2000
Expectation propagation for exponential families M Seeger	211	2005
Computed torque control with nonparametric regression models D Nguyen-Tuong, M Seeger, J Peters 2008 American Control Conference, 212-217, 2008	209	2008
Optimization of k‐space trajectories for compressed sensing by Bayesian experimental design M Seeger, H Nickisch, R Pohmann, B Schölkopf Magnetic Resonance in Medicine: An Official Journal of the International …, 2010	192	2010
Scalable hyperparameter transfer learning V Perrone, R Jenatton, MW Seeger, C Archambeau Advances in neural information processing systems 31, 2018	187	2018

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors