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Publications associées (39)

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

Springer2023

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Gabriel Okasa

Estimation of causal effects using machine learning methods has become an active research field in econometrics. In this paper, we study the finite sample performance of meta-learners for estimation of heterogeneous treatment effects under the usage of sam ...

2022

Estimating network travel time reliability with network partitioning

Nikolaos Geroliminis, Mohammadreza Saeedmanesh

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliabili ...

PERGAMON-ELSEVIER SCIENCE LTD2020

MRI T2 Mapping of the Knee Providing Synthetic Morphologic Images: Comparison to Conventional Turbo Spin-Echo MRI

Tobias Kober, Tom Hilbert

Background: Use of a T2 mapping sequence in addition to the conventional knee MRI protocol increases sensitivity to early cartilage lesions but is time consuming. Purpose: To test the in vitro validity of quantitative data from an accelerated parallel T2 m ...

RADIOLOGICAL SOC NORTH AMERICA2019

A Magnet-Based Timing System to Detect Gate Crossings in Alpine Ski Racing

Kamiar Aminian, Benedikt Fasel

In alpine skiing, intermediate times are usually measured with photocells. However, for practical reasons, the number of intermediate cells is limited to three⁻four, making a detailed timing analysis difficult. In this paper, we propose and validate a magn ...

2019

Magnetization transfer in magnetic resonance fingerprinting

Tobias Kober, Tom Hilbert

Purpose To study the effects of magnetization transfer (MT, in which a semi-solid spin pool interacts with the free pool), in the context of magnetic resonance fingerprinting (MRF). Methods Simulations and phantom experiments were performed to study the im ...

WILEY2019

Perturbation-based inference for diffusion processes: Obtaining effective models from multiscale data

Sebastian Krumscheid

We consider the inference problem for parameters in stochastic differential equation models from discrete time observations (e.g. experimental or simulation data). Specifically, we study the case where one does not have access to observations of the model ...

2018

SpotCaliper: Fast Wavelet-Based Spot Detection with Accurate Size Estimation

Michaël Unser, Daniel Sage, Zsuzsanna Püspöki, John Paul Ward

Motivation: SpotCaliper is a novel wavelet-based image-analysis software providing a fast automatic detection scheme for circular patterns (spots), combined with the precise estimation of their size. It is implemented as an ImageJ plugin with a friendly us ...

Oxford Journals2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Volkan Cevher, Andreas Krause, Jonathan Mark Scarlett, Ilija Bogunovic

We present a new algorithm, truncated variance reduction (TruVaR), that treats Bayesian optimization (BO) and level-set estimation (LSE) with Gaussian processes in a unified fashion. The algorithm greedily shrinks a sum of truncated variances within a set ...

2016

A Collaborative Sensor Fusion Algorithm for Multi-Object Tracking Using a Gaussian Mixture Probability Hypothesis Density Filter

Alcherio Martinoli, Milos Vasic

This paper presents a method for collaborative tracking of multiple vehicles that extends a Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter with a collaborative fusion algorithm. Measurements are preprocessed in a detect-before-track fashio ...

2015

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