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Lightweight HI source finding for next generation radio surveys

Publications associées (76)

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The role of convolutional neural networks in scanning probe microscopy: a review

Georg Fantner

Progress in computing capabilities has enhanced science in many ways. In recent years, various branches of machine learning have been the key facilitators in forging new paths, ranging from categorizing big data to instrumental control, from materials desi ...

BEILSTEIN-INSTITUT2021

A data-driven perspective on the colours of metal-organic frameworks

Berend Smit, Luc Patiny, Seyedmohamad Moosavi, Kevin Maik Jablonka, Mehrdad Asgari, Christopher Patrick Ireland

Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is often used to assess the success of a synthesis. However, predicting the colour of a materi ...

2021

A mathematical dashboard for the analysis of Italian COVID-19 epidemic data

Alfio Quarteroni, Luca Dede', Nicola Parolini

An analysis of the COVID-19 epidemic is proposed on the basis of the epiMOX dashboard (publicly accessible at ) that deals with data of the epidemic trends and outbreaks in Italy from late February 2020. Our analysis provides an immediate appreciation of t ...

WILEY2021

Toward catchment hydro-biogeochemical theories

Andrea Rinaldo, Paolo Benettin, Ilja van Meerveld, Li Li

Headwater catchments are the fundamental units that connect the land to the ocean. Hydrological flow and biogeochemical processes are intricately coupled, yet their respective sciences have progressed without much integration. Reaction kinetic theories tha ...

WILEY2020

Deep neural networks have been empirically successful in a variety of tasks, however their theoretical understanding is still poor. In particular, modern deep neural networks have many more parameters than training data. Thus, in principle they should over ...

EPFL2020

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Claire Marianne Charlotte Capelo

The explosive growth of machine learning in the age of data has led to a new probabilistic and data-driven approach to solving very different types of problems. In this paper we study the feasibility of using such data-driven algorithms to solve classic ph ...

2020

AIDE: Accelerating image‐based ecological surveys with interactive machine learning

Devis Tuia, Benjamin Alexander Kellenberger

Ecological surveys increasingly rely on large‐scale image datasets, typically terabytes of imagery for a single survey. The ability to collect this volume of data allows surveys of unprecedented scale, at the cost of expansive volumes of photo‐interpretati ...

2020

Begun in 2017 and set to be finished at the end of 2020, the "Bergère 2020" Project is set to renovate the buildings in the Nestlé HQ.With a higher accent brought on Building automation, this thesis views itself as an exploratory journey in the literature ...

2020

Introduction: The unprecedented speed and scale of the COVID-19 pandemic necessitated the rapid implementation of untested public health measures to mitigate the consequences of viral spread. In the 8 months that have passed since the first recognized case ...

2020

Recommender System for Responsive Engagement of Senior Adults in Daily Activities

Pearl Pu Faltings, Igor Kulev, Yuan Lu

Understanding and predicting how people change their behavior after an intervention from time series data is an important task for health recommender systems. This task is especially challenging when the time series data is frequently sampled. In this pape ...

SPRINGER INTERNATIONAL PUBLISHING AG2020