Publication

Adaptive Fingers Coordination for Robust Grasp and In-Hand Manipulation Under Disturbances and Unknown Dynamics

Publications associées (30)

A Whale's Tail - Finding the Right Whale in an Uncertain World

Explainable machine learning and uncertainty quantification have emerged as promising approaches to check the suitability and understand the decision process of a data-driven model, to learn new insights from data, but also to get more information about th ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Modelling the Intracellular Environment under Uncertainty, from Post-translational Modification to Metabolic Networks

Robin Alexander Denhardt-Eriksson

Modelling and analysis of biological systems is crucial in order to quantitatively explain and predict their behaviour. The importance of modelling in systems biology becomes even more evident when tackling complex, large systems. Approaches that rely on ...

EPFL2021

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Lubna Dada

Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, ...

Copernicus Publications2021

Theoretical minimum uncertainty of single-molecule localizations using a single-photon avalanche diode array

Edoardo Charbon, Claudio Bruschini, Paul Mos, Arin Can Ülkü, Daniel Fan

Single-photon avalanche diode (SPAD) arrays can be used for single-molecule localization microscopy (SMLM) because of their high frame rate and lack of readout noise. SPAD arrays have a binary frame output, which means photon arrivals should be described a ...

OPTICAL SOC AMER2021

Deep Gaussian denoiser epistemic uncertainty and decoupled dual-attention fusion

Sabine Süsstrunk, Majed El Helou, Xiaoyu Lin, Xiaoqi Ma

Following the performance breakthrough of denoising networks, improvements have come chiefly through novel architecture designs and increased depth. While novel denoising networks were designed for real images coming from different distributions, or for sp ...

2021

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Daniel Kuhn, Tobias Sutter, Andreas Krause

Training models that perform well under distribution shifts is a central challenge in machine learning. In this paper, we introduce a modeling framework where, in addition to training data, we have partial structural knowledge of the shifted test distribut ...

2021

A consistent safety format and design approach for brittle systems and application to textile reinforced concrete structures

Aurelio Muttoni, Miguel Fernández Ruiz, Patrick Lorenzo Valeri, Qianhui Yu

Design and verification of structures in modern codes of practice account for a safety format, ensuring that the probability of failure does not exceed a given threshold. Although specific safety formats are proposed in some cases for special types of stru ...

2021

A Unified Theory of Robust and Distributionally Robust Optimization via the Primal-Worst-Equals-Dual-Best Principle

Daniel Kuhn, Jianzhe Zhen, Wolfram Wiesemann

Robust and distributionally robust optimization are modeling paradigms for decision-making under uncertainty where the uncertain parameters are only known to reside in an uncertainty set or are governed by any probability distribution from within an ambigu ...

2023

Experimental characterisation of textile compaction response: A benchmark exercise

Véronique Michaud, Baris Çaglar, Christophe Lopez

This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure ...

2021

Evaluating measurement uncertainty in Brillouin distributed optical fibre sensors using image denoising

Luc Thévenaz, Marcelo Alfonso Soto Hernandez, Zhisheng Yang, Simon Adrien Zaslawski

In 2016, our research team proposed in an issue of Nature Communications1 the use of multidimensional signal processing, especially image denoising techniques, to improve the signal-to-noise ratio (SNR) of distributed optical ﬁbre sensors. The beneﬁts of t ...

Nature Research2021