
Scalable mixeddomain Gaussian processes
Gaussian process (GP) models that combine both categorical and continuou...
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Bayesian inference of ODEs with Gaussian processes
Recent machine learning advances have proposed blackbox estimation of u...
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ContinuousTime ModelBased Reinforcement Learning
Modelbased reinforcement learning (MBRL) approaches rely on discreteti...
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Sampleefficient reinforcement learning using deep Gaussian processes
Reinforcement learning provides a framework for learning to control whic...
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Longitudinal Variational Autoencoder
Longitudinal datasets measured repeatedly over time from individual subj...
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Learning continuoustime PDEs from sparse data with graph neural networks
The behavior of many dynamical systems follow complex, yet still unknown...
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An interpretable probabilistic machine learning method for heterogeneous longitudinal studies
Identifying risk factors from longitudinal data requires statistical too...
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Latent Gaussian process with composite likelihoods for datadriven disease stratification
Datadriven techniques for identifying disease subtypes using medical re...
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ODE^2VAE: Deep generative second order ODEs with Bayesian neural networks
We present Ordinary Differential Equation Variational AutoEncoder (ODE^...
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Deep learning with differential Gaussian process flows
We propose a novel deep learning paradigm of differential flows that lea...
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Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matching
We introduce a novel paradigm for learning nonparametric drift and diff...
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Bayesian Metabolic Flux Analysis reveals intracellular flux couplings
Metabolic flux balance analyses are a standard tool in analysing metabol...
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Learning unknown ODE models with Gaussian processes
In conventional ODE modelling coefficients of an equation driving the sy...
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mGPfusion: Predicting protein stability changes with Gaussian process kernel learning and data fusion
Proteins are commonly used by biochemical industry for numerous processe...
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NonStationary Gaussian Process Regression with Hamiltonian Monte Carlo
We present a novel approach for fully nonstationary Gaussian process re...
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Harri Lähdesmäki
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