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Lehel Csató
Lehel Csató
Department of Computer Science and Mathematics, Babeș-Bolyai University, Cluj-Napoca
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Año
Sparse on-line Gaussian processes
L Csató, M Opper
Neural computation 14 (3), 641-668, 2002
10132002
Gaussian processes: iterative sparse approximations
L Csató
Aston University, 2002
1822002
Sparse representation for Gaussian process models
L Csató, M Opper
Advances in neural information processing systems 13, 2000
1762000
Alignment-based transfer learning for robot models
B Bocsi, L Csató, J Peters
The 2013 international joint conference on neural networks (IJCNN), 1-7, 2013
872013
Efficient approaches to Gaussian process classification
L Csató, E Fokoué, M Opper, B Schottky, O Winther
Advances in neural information processing systems 12, 1999
791999
Learning inverse kinematics with structured prediction
B Bócsi, D Nguyen-Tuong, L Csató, B Schoelkopf, J Peters
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011
682011
Active learning with clustering
Z Bodó, Z Minier, L Csató
Active Learning and Experimental Design workshop In conjunction with AISTATS …, 2011
552011
TAP Gibbs free energy, belief propagation and sparsity
L Csató, M Opper, O Winther
Advances in Neural Information Processing Systems 14, 2001
432001
Bayesian analysis of the scatterometer wind retrieval inverse problem: some new approaches
D Cornford, L Csató, DJ Evans, M Opper
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2004
402004
Wikipedia-based kernels for text categorization
Z Minier, Z Bodo, L Csato
Ninth International Symposium on Symbolic and Numeric Algorithms for …, 2007
372007
Sequential, Bayesian geostatistics: a principled method for large data sets
D Cornford, L Csató, M Opper
Geographical Analysis 37 (2), 183-199, 2005
322005
Approximate inference for robust Gaussian process regression
M Kuss, T Pfingsten, L Csató, CE Rasmussen
Max Planck Institute for Biological Cybernetics, 2005
272005
Active learning with bayesian UNet for efficient semantic image segmentation
IC Saidu, L Csató
Journal of Imaging 7 (2), 37, 2021
162021
Learning tracking control with forward models
B Bócsi, P Hennig, L Csató, J Peters
2012 IEEE International Conference on Robotics and Automation, 259-264, 2012
162012
Bayesian network classifier for medical data analysis
BĄ Reiz, L Csató
International Journal of Computers Communications & Control 4 (1), 65-72, 2009
152009
Tree-like bayesian network classifiers for surgery survival chance prediction
B Reiz, L Csató
Proceedings of International Conference on Computers, Communications and …, 2008
122008
Linear spectral hashing
Z Bodó, L Csató
Neurocomputing 141, 117-123, 2014
112014
Projected sequential Gaussian processes: A C++ tool for interpolation of large datasets with heterogeneous noise
R Barillec, B Ingram, D Cornford, L Csató
Computers & geosciences 37 (3), 295-309, 2011
92011
Online learning of wind-field models
L Csató, D Cornford, M Opper
International Conference on Artificial Neural Networks, 300-307, 2001
8*2001
A hybrid approach for scholarly information extraction
B Zalán, L CSATÓ
Studia Universitatis Babeș-Bolyai Informatica, 5-16, 2017
72017
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