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Multi-task learning for subthalamic nucleus identification in deep brain stimulation.

, , and . Int. J. Machine Learning & Cybernetics, 9 (7): 1181-1192 (2018)

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Sparse Convolved Gaussian Processes for Multi-output Regression., and . NIPS, page 57-64. Curran Associates, Inc., (2008)Computationally Efficient Convolved Multiple Output Gaussian Processes., and . J. Mach. Learn. Res., (2011)Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems., , and . IEEE Trans. Automat. Contr., 64 (7): 2953-2960 (2019)Kernels for Vector-Valued Functions: A Review., , and . Foundations and Trends in Machine Learning, 4 (3): 195-266 (2012)Linear Latent Force Models Using Gaussian Processes., , and . IEEE Trans. Pattern Anal. Mach. Intell., 35 (11): 2693-2705 (2013)Generalized Wishart processes for interpolation over diffusion tensor fields., , and . CoRR, (2016)Fast Kernel Approximations for Latent Force Models and Convolved Multiple-Output Gaussian processes., and . UAI, page 835-844. AUAI Press, (2018)Dynamic Hand Gesture Recognition Using Generalized Time Warping and Deep Belief Networks., , , , and . ISVC (2), volume 9475 of Lecture Notes in Computer Science, page 682-691. Springer, (2015)Bayesian Shape Models with Shape Priors for MRI Brain Segmentation., , and . ISVC (2), volume 8888 of Lecture Notes in Computer Science, page 851-860. Springer, (2014)Impulse Response Estimation of Linear Time-Invariant Systems Using Convolved Gaussian Processes and Laguerre Functions., and . CIARP, volume 10657 of Lecture Notes in Computer Science, page 281-288. Springer, (2017)