Publications related to Non-linear interpolation and adaptive sampling of scattering parameters

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Benjamin Bejar Haro, Adam James Scholefield, Golnooshsadat Elhami, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

Safe Adaptive Importance Sampling

Martin Jaggi, Sebastian Urban Stich, Anant Raj

Importance sampling has become an indispensable strategy to speed up optimization algorithms for large-scale applications. Improved adaptive variants - using importance values defined by the complete gradient information which changes during optimization - ...

2017

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Anatole von Lilienfeld, Nicholas John Browning

The training of molecular models of quantum mechanical properties based on statistical machine learning requires large data sets which exemplify the map from chemical structure to molecular property. Intelligent a priori selection of training examples is o ...

2017

Quasi-random numbers for copula models

Mathieu Jacques David Cambou

The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such as the conditional distribution method (based on a one-to-one transformatio ...

Springer2017

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Matthieu Martin Jean-André Simeoni

Estimating intensity fields of stochastic phenomenons is of crucial interest in many scientific applications. Typical experimental setups involve an acquisition system, that subsequently filters and samples the probed intensity field. This equivalently def ...

2016

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Satoshi Takahama, Robin Lewis Modini

The composition and properties of atmospheric organic aerosols (OAs) change on timescales of minutes to hours. However, some important OA characterization techniques typically require greater than a few hours of sample-collection time (e.g., Fourier transf ...

Copernicus GmbH2016

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Adrien Georges Jean Besson, Olivier Bernard

The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with prom ...

Ieee2016

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Non-linear interpolation and adaptive sampling of scattering parameters

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Sampling at unknown locations: Uniqueness and reconstruction under constraints

Safe Adaptive Importance Sampling

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Quasi-random numbers for copula models

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Shapes from Pixels

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Random sampling of bandlimited signals on graphs

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Safe Adaptive Importance Sampling

Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties

Random sampling of bandlimited signals on graphs

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Quasi-random numbers for copula models

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Shapes from Pixels

Sampling Sparse Signals on the Sphere: Algorithms and Applications