Temporally Consistent Snow Cover Estimation from Noisy, Irregularly Sampled Measurements

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We present a voxel-wise Bayesian multi-compartment T2 relaxometry fitting method based on Hamiltonian Markov Chain Monte Carlo (HMCMC) sampling. The T 2 spectrum is modeled as a mixture of truncated Gaussian components, which involves the estimation of par ...

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Markov chains that describe interacting subsystems suffer from state space explosion but lead to highly structured matrices. In this work, we propose a novel tensor-based algorithm to address such tensor-structured Markov chains. Our algorithm combines a t ...

In the first part of this thesis, we present and compare several approaches for the determination of the steady-state of large-scale Markov chains with an underlying low-rank tensor structure. Such structure is, in our context of interest, associated with ...

Temporally Consistent Snow Cover Estimation from Noisy, Irregularly Sampled Measurements

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Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

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Unsupervised algorithm for disaggregating low-sampling-rate electricity consumption of households

End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

Efficient Learning from Comparisons

Multigrid Methods Combined With Low-Rank Approximation For Tensor-Structured Markov Chains

Low-rank tensor methods for large Markov chains and forward feature selection methods