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Data wrangling

Related publications (184)

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

Lithium tantalate photonic integrated circuits for volume manufacturing

Tobias Kippenberg

Dataset for the manuscript "Lithium tantalate photonic integrated circuits for volume manufacturing". DOI: 10.1038/s41586-024-07369-1 Contains all raw data and code used to produce the Figures and Extended Data Figures in the manuscript. ...

Zenodo2023

Robustness of Local Predictions in Atomistic Machine Learning Models

Michele Ceriotti, Federico Grasselli, Sanggyu Chong, Chiheb Ben Mahmoud

Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven si ...

Washington2023

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-Based Filters

Colin Neil Jones, Yingzhao Lian, Jicheng Shi

Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency between any known underlying physical laws and a data-driven decision-making process, preprocessin ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dataset for the paper High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing

Aleksandra Radenovic, Andras Kis, Martina Lihter, Mukesh Kumar Tripathi, Mukeshchand Thakur, Andrey Chernev, Nianduo Cai, Yunfei Teng, Michal Daniel Macha, Yanfei Zhao, Miao Zhang

Information regarding the Dataset, corresponding to the paper: “Thakur, M., Cai, N., Zhang, M. et al. High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing. npj 2D Mater Appl 7, 11 (2023). https://doi.org/10.1038/s41 ...

EPFL Infoscience2023

Methodology for selecting measurement points that optimize information gain for model updating

Ian Smith, Numa Joy Bertola

Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...

2023

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

Sila Karatas

This text, accompanied by a ‘gospel’ that I made by montaging the US-recorded captions, is an attempt for re-narrating Marshall Plan’s discourse on the working class, aka the so-called ‘free labor’ of the US against the ‘communist labor’ of the “Soviet thr ...

EPFL Press2023

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Michaël Unser, Pakshal Narendra Bohra, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer, Stanislas Ducotterd

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

EPFL Infoscience2023

An end-to-end pipeline for historical censuses processing

Lucas Arnaud André Rappo, Rémi Guillaume Petitpierre, Marion Kramer

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

2023

Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning

Kathrin Grosse, Sebastiano Vascon

The success of machine learning is fueled by the increasing availability of computing power and large training datasets. The training data is used to learn new models or update existing ones, assuming that it is sufficiently representative of the data that ...

2023

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