Search Results - "Alvarez, Mauricio A"

Linear Latent Force Models Using Gaussian Processes by Alvarez, M. A., Luengo, D., Lawrence, N. D.

“…Purely data-driven approaches for machine learning present difficulties when data are scarce relative to the complexity of the model or when the model is…”
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Gaussian Process Latent Force Models for Learning and Stochastic Control of Physical Systems by Sarkka, Simo, Alvarez, Mauricio A., Lawrence, Neil D.

“…This paper is concerned with learning and stochastic control in physical systems that contain unknown input signals. These unknown signals are modeled as…”
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Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison by Zuluaga, Carlos D., Álvarez, Mauricio A., Giraldo, Eduardo

“…•Three robust Kalman filters are applied to one-step-ahead forecast of wind speed.•We provide a detailed description of differences among robust Kalman…”
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Bayesian Probabilistic Power Flow Analysis Using Jacobian Approximate Bayesian Computation by Zuluaga, Carlos David, Alvarez, Mauricio A.

“…A probabilistic power flow (PPF) study is an essential tool for the analysis and planning of a power system when specific variables are considered as random…”
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A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multioutput Gaussian Process Model by Giraldo, Juan-Jose, Alvarez, Mauricio A.

“…A recent novel extension of multioutput Gaussian processes (GPs) handles heterogeneous outputs, assuming that each output has its own likelihood function. It…”
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Correlated Chained Gaussian Processes for Modelling Citizens Mobility Using a Zero-Inflated Poisson Likelihood by Giraldo, Juan-Jose, Zhang, Jie, Alvarez, Mauricio A.

“…Modelling the mobility of people in a city depends on counting data with inherent problems of overdispersion. Such dispersion issues are caused by massive…”
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Large scale multi-output multi-class classification using Gaussian processes by Ma, Chunchao, Álvarez, Mauricio A.

“…Multi-output Gaussian processes (MOGPs) can help to improve predictive performance for some output variables, by leveraging the correlation with other output…”
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Adversarial vulnerability bounds for Gaussian process classification by Smith, Michael Thomas, Grosse, Kathrin, Backes, Michael, Álvarez, Mauricio A.

“…Protecting ML classifiers from adversarial examples is crucial. We propose that the main threat is an attacker perturbing a confidently classified input to…”
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Predicting socioeconomic indicators using transfer learning on imagery data: an application in Brazil by Castro, Diego A., Álvarez, Mauricio A.

“…Censuses and other surveys responsible for gathering socioeconomic data are expensive and time consuming. For this reason, in poor and developing countries…”
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Bayesian inversion of a diffusion model with application to biology by Croix, Jean-Charles, Durrande, Nicolas, Alvarez, Mauricio A.

“…A common task in experimental sciences is to fit mathematical models to real-world measurements to improve understanding of natural phenomenon…”
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Switched Latent Force Models for Reverse-Engineering Transcriptional Regulation in Gene Expression Data by Lopez-Lopera, Andres F., Alvarez, Mauricio A.

“…To survive environmental conditions, cells transcribe their response activities into encoded mRNA sequences in order to produce certain amounts of protein…”
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Physically-Inspired Gaussian Process Models for Post-Transcriptional Regulation in Drosophila by Lopez-Lopera, Andres F., Durrande, Nicolas, Alvarez, Mauricio A.

“…The regulatory process of Drosophila is thoroughly studied for understanding a great variety of biological principles. While pattern-forming gene networks are…”
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Multi-output prediction of dose–response curves enables drug repositioning and biomarker discovery by Gutierrez, Juan-José Giraldo, Lau, Evelyn, Dharmapalan, Subhashini, Parker, Melody, Chen, Yurui, Álvarez, Mauricio A., Wang, Dennis

“…Drug response prediction is hampered by uncertainty in the measures of response and selection of doses. In this study, we propose a probabilistic multi-output…”
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Tensor decomposition processes for interpolation of diffusion magnetic resonance imaging by Vargas-Cardona, Hernán Darío, Orozco, Álvaro A., Álvarez, Andrés M., Álvarez, Mauricio A.

“…•A Novel probabilistic framework for interpolation of dMRI-HOT is proposed.•The framework is based on Gaussian processes combined with tensor…”
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Multi-task learning for subthalamic nucleus identification in deep brain stimulation by Vargas Cardona, Hernán Darío, Álvarez, Mauricio A., Orozco, Álvaro A.

“…Deep brain stimulation (DBS) of Subthalamic nucleus (STN) is the most successful treatment for advanced Parkinson’s disease. Localization of the STN through…”
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Dynamic facial landmarking selection for emotion recognition using Gaussian processes by García, Hernán F., Álvarez, Mauricio A., Orozco, Álvaro A.

“…Facial features are the basis for the emotion recognition process and are widely used in affective computing systems. This emotional process is produced by a…”
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A machine learning approach to support deep brain stimulation programming by Gómez-Orozco, Viviana, De La Pava Panche, Iván, Álvarez-Meza, Andrés Marino, Álvarez-López, Mauricio Alexander, Orozco-Gutiérrez, Álvaro Ángel

“…Adjusting the stimulation parameters is a challenge in deep brain stimulation (DBS) therapy due to the vast number of different configurations available. As a…”
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Short-term time series prediction using Hilbert space embeddings of autoregressive processes by Valencia, Edgar A., Álvarez, Mauricio A.

“…Linear autoregressive models serve as basic representations of discrete time stochastic processes. Different attempts have been made to provide non-linear…”
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Prospective prediction of childhood body mass index trajectories using multi-task Gaussian processes by Leroy, Arthur, Gupta, Varsha, Tint, Mya Thway, Ooi, Delicia Shu Qin, Yap, Fabian, Lek, Ngee, Godfrey, Keith M., Chong, Yap Seng, Lee, Yung Seng, Eriksson, Johan G., Álvarez, Mauricio A., Michael, Navin, Wang, Dennis

“…Abstract Background Body mass index (BMI) trajectories have been used to assess the growth of children with respect to their peers, and to anticipate future…”
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Modelling calibration uncertainty in networks of environmental sensors by Smith, Michael Thomas, Ross, Magnus, Ssematimba, Joel, Álvarez, Mauricio A, Bainomugisha, Engineer, Wilkinson, Richard

“…Abstract Networks of low-cost environmental sensors are becoming ubiquitous, but often suffer from poor accuracies and drift. Regular colocation with reference…”
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