| A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multioutput Gaussian Process Model | 0 | 0.34 | 2022 |
| Correlated Chained Gaussian Processes for Modelling Citizens Mobility Using a Zero-Inflated Poisson Likelihood | 0 | 0.34 | 2022 |
| Multi-task Causal Learning with Gaussian Processes | 0 | 0.34 | 2020 |
| Variational bridge constructs for approximate Gaussian process regression. | 0 | 0.34 | 2019 |
| Fast Kernel Approximations For Latent Force Models And Convolved Multiple-Output Gaussian Processes | 2 | 0.37 | 2018 |
| Nonlinear Probabilistic Latent Variable Models for Groupwise Correspondence Analysis in Brain Structures | 0 | 0.34 | 2018 |
| A DTW-Based Representation to Support Static Sign Language Recognition from Binary Images. | 0 | 0.34 | 2018 |
| Non-Stationary Generalized Wishart Processes For Enhancing Resolution Over Diffusion Tensor Fields | 0 | 0.34 | 2018 |
| Heterogeneous Multi-output Gaussian Process Prediction. | 2 | 0.38 | 2018 |
| Multi-task learning for subthalamic nucleus identification in deep brain stimulation. | 1 | 0.37 | 2018 |
| Physically-inspired Gaussian processes for transcriptional regulation in Drosophila melanogaster. | 0 | 0.34 | 2018 |
| Gaussian Process Regression for Binned Data. | 0 | 0.34 | 2018 |
| Sparse Gaussian Process Audio Source Separation Using Spectrum Priors In The Time-Domain | 1 | 0.35 | 2018 |
| Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes. | 5 | 0.42 | 2017 |
| Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems. | 0 | 0.34 | 2017 |
| Impulse Response Estimation of Linear Time-Invariant Systems Using Convolved Gaussian Processes and Laguerre Functions. | 0 | 0.34 | 2017 |
| Non-stationary Multi-output Gaussian Processes for Enhancing Resolution over Diffusion Tensor Fields. | 0 | 0.34 | 2017 |
| SVM-based feature selection methods for emotion recognition from multimodal data. | 3 | 0.39 | 2017 |
| Dynamic facial landmarking selection for emotion recognition using Gaussian processes. | 0 | 0.34 | 2017 |
| Approximate Probabilistic Power Flow | 0 | 0.34 | 2016 |
| A Tucker decomposition process for probabilistic modeling of diffusion magnetic resonance imaging. | 0 | 0.34 | 2016 |
| Generalized Wishart Processes for Interpolation Over Diffusion Tensor Fields | 2 | 0.50 | 2016 |
| Groupwise Shape Correspondences on 3D Brain Structures Using Probabilistic Latent Variable Models. | 0 | 0.34 | 2015 |
| Spatial-Dependent Similarity Metric Supporting Multi-Atlas Mri Segmentation | 0 | 0.34 | 2015 |
| Improving Diffusion Tensor Estimation Using Adaptive And Optimized Filtering Based On Local Similarity | 0 | 0.34 | 2015 |
| Global And Local Gaussian Process For Multioutput And Treed Data | 0 | 0.34 | 2015 |
| A Gaussian Process Emulator For Estimating The Volume Of Tissue Activated During Deep Brain Stimulation | 0 | 0.34 | 2015 |
| NEURONAV: A Tool for Image-Guided Surgery - Application to Parkinson's Disease. | 0 | 0.34 | 2015 |
| Dynamic Hand Gesture Recognition Using Generalized Time Warping and Deep Belief Networks. | 1 | 0.41 | 2015 |
| Gaussian Processes for Slice-Based Super-Resolution MR Images. | 0 | 0.34 | 2015 |
| Convolved Multi-Output Gaussian Processes For Semi-Supervised Learning | 1 | 0.36 | 2015 |
| Peripheral Nerves Segmentation In Ultrasound Images Using Non-Linear Wavelets And Gaussian Processes | 0 | 0.34 | 2015 |
| A Parzen-Based Distance Between Probability Measures As An Alternative Of Summary Statistics In Approximate Bayesian Computation | 1 | 0.43 | 2015 |
| Peripheral Nerve Segmentation Using Speckle Removal And Bayesian Shape Models | 1 | 0.34 | 2015 |
| Kernel Centered Alignment Supervised Metric For Multi-Atlas Segmentation | 1 | 0.36 | 2015 |
| Bayesian Shape Models with Shape Priors for MRI Brain Segmentation. | 2 | 0.44 | 2014 |
| Automatic Recognition of Microcalcifications in Mammography Images through Fractal Texture Analysis. | 1 | 0.36 | 2014 |
| Sparse representation of MER signals for localizing the Subthalamic Nucleus in Parkinson's disease surgery. | 0 | 0.34 | 2014 |
| Gaussian Process Dynamical Models for Emotion Recognition. | 1 | 0.37 | 2014 |
| Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment. | 1 | 0.37 | 2014 |
| Latent force models for describing transcriptional regulation processes in the embryo development problem for the Drosophila melanogaster. | 0 | 0.34 | 2014 |
| A latent force model for describing electric propagation in deep brain stimulation: a simulation study. | 0 | 0.34 | 2014 |
| Linear Latent Force Models Using Gaussian Processes | 25 | 1.36 | 2013 |
| Feature Selection For Multimodal Emotion Recognition In The Arousal-Valence Space | 5 | 0.53 | 2013 |
| Dynamic physiological signal analysis based on Fisher kernels for emotion recognition. | 1 | 0.37 | 2013 |
| Unsupervised learning applied in MER and ECG signals through Gaussians mixtures with the Expectation-Maximization algorithm and Variational Bayesian Inference. | 0 | 0.34 | 2013 |
| Neurozone: On-Line Recognition Of Brain Structures In Stereotactic Surgery - Application To Parkinson'S Disease | 0 | 0.34 | 2012 |
| Kernels for Vector-Valued Functions: A Review | 48 | 1.81 | 2012 |
| Computationally Efficient Convolved Multiple Output Gaussian Processes | 43 | 2.13 | 2011 |
| Switched Latent Force Models for Movement Segmentation. | 14 | 0.86 | 2010 |
