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A robust method for inverse transport modelling of atmospheric emissions using blind outlier detection

Related publications (29)

Distributional Robustness in Mechanism Design

Mechanism design theory examines the design of allocation mechanisms or incentive systems involving multiple rational but self-interested agents and plays a central role in many societally important problems in economics. In mechanism design problems, agen ...

EPFL2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Optimum design of frame structures from a stock of reclaimed elements

Corentin Jean Dominique Fivet, Jan Friedrich Georg Brütting, Gennaro Senatore

This paper presents optimization methods to design frame structures from a stock of existing elements. These methods are relevant when reusing structural elements over multiple service lives. Reuse has the potential to reduce the environmental impact of bu ...

2020

Atmospheric evolution of molecular-weight-separated brown carbon from biomass burning

Athanasios Nenes, Kalliopi Violaki

Biomass burning is a major source of atmospheric brown carbon (BrC), and through its absorption of UV/VIS radiation, it can play an important role in the planetary radiative balance and atmospheric photochemistry. The considerable uncertainty of BrC impact ...

Copernicus GmbH2019

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Ilija Bogunovic

The central task in many interactive machine learning systems can be formalized as the sequential optimization of a black-box function. Bayesian optimization (BO) is a powerful model-based framework for \emph{adaptive} experimentation, where the primary go ...

EPFL2019

ActiveAx(ADD): Toward non-parametric and orientationally invariant axon diameter distribution mapping using PGSE

Jean-Philippe Thiran, David Paul Roger Romascano, Alessandro Daducci, Muhamed Barakovic, Jonathan Rafael Patino Lopez, Tim Bjørn Dyrby

Purpose Non-invasive axon diameter distribution (ADD) mapping using diffusion MRI is an ill-posed problem. Current ADD mapping methods require knowledge of axon orientation before performing the acquisition. Instead, ActiveAx uses a 3D sampling scheme to e ...

Wiley2020

On flow duration curve modelling in Alpine catchments

Ana Clara Pereira Barbosa Santos

Mountain regions are considered to be the natural "water towers" of the world due to their importance as sources of many rivers. Reliable tools to estimate the availability and variability of streamflows in such regions are still rare. In this context, the ...

EPFL2019

Robust T2 Relaxometry with Hamiltonian MCMC for Myelin Water Fraction Estimation

Jean-Philippe Thiran, Marco Pizzolato, Thomas Yu

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 ...

IEEE2019

Fast and robust estimation of NODDI parameters using non-Gaussian noise models and spatial regularization

Jean-Philippe Thiran, Alessandro Daducci, Erick Jorge Canales Rodriguez

In this study, we developed a robust inversion algorithm to estimate the Neurite Orientation Dispersion and Density Imaging (NODDI) model. It is based on the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. However, in contrast ...

2018