Efficient Approaches to Gaussian Process Classification. - Lehel Csató; Ernest Fokoué; Manfred Opper; Bernhard Schottky; Ole Winther (NIPS, 1999)

Sparse Representation for Gaussian Process Models. - Lehel Csató; Manfred Opper (NIPS, 2000)

Online Approximations for Wind-Field Models. - Lehel Csató; Dan Cornford; Manfred Opper (ICANN, 2001)

TAP Gibbs Free Energy, Belief Propagation and Sparsity. - Lehel Csató; Manfred Opper; Ole Winther (NIPS, 2001)

Sparse On-Line Gaussian Processes. - Lehel Csató; Manfred Opper (Neural Comput., 2002)

Tractable inference for probabilistic data models. - Lehel Csató; Manfred Opper; Ole Winther (Complex., 2003)

Kernel PCA based clustering for inducing features in text categorization. - Zsolt Minier; Lehel Csató (ESANN, 2007)

Wikipedia-Based Kernels for Text Categorization. - Zsolt Minier; Zalán Bodó; Lehel Csató (SYNASC, 2007)

Prufer Number Encoding for Genetic Bayesian Network Structure Learning Algorithm. - Beáta Reiz; Lehel Csató; Dan Dumitrescu (SYNASC, 2008)

Dirichlet process-based component detection in state-space models. - Botond Bocsi; Lehel Csató (ESANN, 2009)

Bayesian Network Classifier for Medical Data Analysis. - Beáta Reiz; Lehel Csató (Int. J. Comput. Commun. Control, 2009)

Hierarchical and Reweighting Cluster Kernels for Semi-Supervised Learning. - Zalán Bodó; Lehel Csató (Int. J. Comput. Commun. Control, 2010)

Improving Gaussian Process Value Function Approximation in Policy Gradient Algorithms. - Hunor Jakab; Lehel Csató (ICANN (2), 2011)

Learning inverse kinematics with structured prediction. - Botond Bocsi; Duy Nguyen-Tuong; Lehel Csató; Bernhard Schölkopf; Jan Peters 001 (IROS, 2011)

Projected sequential Gaussian processes: A C++ tool for interpolation of large datasets with heterogeneous noise. - Remi Louis Barillec; Ben Ingram; Dan Cornford; Lehel Csató (Comput. Geosci., 2011)

Active Learning with Clustering. - Zalán Bodó; Zsolt Minier; Lehel Csató (Active Learning and Experimental Design @ AISTATS, 2011)

Manifold-based non-parametric learning of action-value functions. - Hunor Jakab; Lehel Csató (ESANN, 2012)

Learning tracking control with forward models. - Botond Bocsi; Philipp Hennig; Lehel Csató; Jan Peters 001 (ICRA, 2012)

Improving kernel locality-sensitive hashing using pre-images and bounds. - Zalán Bodó; Lehel Csató (IJCNN, 2012)

Reinforcement learning with guided policy search using Gaussian processes. - Hunor Jakab; Lehel Csató (IJCNN, 2012)

Hessian Corrected Input Noise Models. - Botond Attila Bócsi; Lehel Csató (ICANN, 2013)

Novel Feature Selection and Kernel-Based Value Approximation Method for Reinforcement Learning. - Hunor Sandor Jakab; Lehel Csató (ICANN, 2013)

Alignment-based transfer learning for robot models. - Botond Bocsi; Lehel Csató; Jan Peters 001 (IJCNN, 2013)

Augmented hashing for semi-supervised scenarios. - Zalán Bodó; Lehel Csató (ESANN, 2014)

Simulation-Extrapolation Gaussian Processes for Input Noise Modeling. - Botond Bocsi; Hunor Jakab; Lehel Csató (SYNASC, 2014)

Indirect robot model learning for tracking control. - Botond Attila Bócsi; Lehel Csató; Jan Peters 001 (Adv. Robotics, 2014)

Linear spectral hashing. - Zalán Bodó; Lehel Csató (Neurocomputing, 2014)

Finding Patterns in Visualizations of Programs. - Catalin F. Perticas; Bipin Indurkhya; Razvan V. Florian; Lehel Csató (PPIG, 2017)

Distortion Estimation Through Explicit Modeling of the Refractive Surface. - Szabolcs Pável; Csanád Sándor; Lehel Csató (ICANN (3), 2019)

Single View Distortion Correction using Semantic Guidance. - Szabolcs-Botond Lorincz; Szabolcs Pável; Lehel Csató (IJCNN, 2019)

Pruning CNN's with Linear Filter Ensembles. - Csanád Sándor; Szabolcs Pável; Lehel Csató (ECAI, 2020)

Active Learning with Bayesian UNet for Efficient Semantic Image Segmentation. - Isah Charles Saidu; Lehel Csató (J. Imaging, 2021)

Applying Deep Q-learning for Multi-agent Cooperative-Competitive Environments. - Anikó Kopacz; Lehel Csató; Camelia Chira (SOCO, 2022)

Neural Network Pruning based on Filter Importance Values Approximated with Monte Carlo Gradient Estimation. - Csanád Sándor; Szabolcs Pável; Lehel Csató (VISIGRAPP (5: VISAPP), 2022)

Standardized feature extraction from pairwise conflicts applied to the train rescheduling problem. - Anikó Kopacz; Ágnes Mester; Sándor Kolumbán; Lehel Csató (CoRR, 2022)

Wavelet-Based Prototype Networks. - Tamás Kaszta; Hanna-Georgina Lieb; Lehel Csató (SISY, 2023)

Evaluating cooperative-competitive dynamics with deep Q-learning. - Anikó Kopacz; Lehel Csató; Camelia Chira (Neurocomputing, 2023)

Wavelet-Based Prototype Learning for Medical Image Classification. - Hanna-Georgina Lieb; Tamás Kaszta; Lehel Csató (SISY, 2024)

Deep multiple affinity model for proposal-free single instance segmentation. - Isah Charles Saidu; Lehel Csató (Int. J. Comput. Vis. Robotics, 2024)