Concept

Data wrangling

Publications associées (184)

Generic Semantic Segmentation of Historical Maps

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre

Research in automatic map processing is largely focused on homogeneous corpora or even individual maps, leading to inflexible models. Based on two new corpora, the first one centered on maps of Paris and the second one gathering maps of cities from all ove ...

2021

From the Heroic Age to today: What diatoms from Shackleton's Nimrod expedition can tell us about the ecological trajectory of Antarctic ponds

Tyler Joe Kohler

Biological invasion and environmental change pose major threats to ecosystems. While long-term ecological change is commonly evaluated through sediment cores in lakes, it is generally not feasible for smaller ponds, and spatial resolution is limited. Here, ...

WILEY2021

Cleaning Denial Constraint Violations through Relaxation

Anastasia Ailamaki, Manolis Karpathiotakis, Styliani Asimina Giannakopoulou

Data cleaning is a time-consuming process that depends on the data analysis that users perform. Existing solutions treat data cleaning as a separate offline process that takes place before analysis begins. Applying data cleaning before analysis assumes a p ...

ASSOC COMPUTING MACHINERY2020

Query-driven Repair of Functional Dependency Violations

Anastasia Ailamaki, Manolis Karpathiotakis, Styliani Asimina Giannakopoulou

IEEE COMPUTER SOC2020

Seismic Vulnerability Assessment at Large Scale – City of Geneva

Babak Haftgoli Bakhtiari

In order to evaluate the seismic vulnerability at large scale, it is necessary to gain awareness of the soil properties, types of materials used in the construction of buildings during different periods, the construction standards of each period, different ...

2020

Adaptive partitioning and indexing for in situ query processing

Anastasia Ailamaki, Manolis Karpathiotakis, Ioannis Alagiannis, Manoussos Gavriil Athanassoulis, Matthaios Alexandros Olma

The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. To alleviate the loading cost, in ...

SPRINGER2020

Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks

Olivier Sauter, Alessandro Pau

In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...

TAYLOR & FRANCIS INC2020

The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models

André Anjos

The segmentation of the retinal vasculature from eye fundus images represents one of the most fundamental tasks in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures ...

2020

On The Choice of Graph Neural Network Architectures

Pascal Frossard, Guillermo Ortiz Jimenez, Clément Arthur Yvon Vignac

Seminal works on graph neural networks have primarily targeted semi-supervised node classification problems with few observed labels and high-dimensional signals. With the development of graph networks, this setup has become a de facto benchmark for a sign ...

2020

A parallelized, automated platform enabling individual or sequential ChIP of histone marks and transcription factors

Bart Deplancke, Vincent Roland Julien Gardeux, Jia Yuan Jiang, Riccardo Dainese, Daniel Alpern, Antonio Carlos Alves Meireles Filho, Gerard Llimos Aubach

Despite its popularity, chromatin immunoprecipitation followed by sequencing (ChIP-seq) remains a tedious (>2 d), manually intensive, low-sensitivity and low-throughput approach. Here, we combine principles of microengineering, surface chemistry, and molec ...

NATL ACAD SCIENCES2020

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