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researcher

A. Vespignani

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CY1
  • stat.AP1
  • stat.OT1

identity via Semantic Scholar / OpenAlex

most citedA machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models

102 citations · 104 across the 3 of their papers we have counts for

collaborators

3 papers

stat.AP2020

An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time

Nicole E. Kogan, Leonardo Clemente, Parker Liautaud +14

Non-pharmaceutical interventions (NPIs) have been crucial in curbing COVID-19 in the United States (US). Consequently, relaxing NPIs through a phased re-opening of the US amid stil…

cs.CY2020★ 2 cited

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment

Mirco Nanni, Gennady Andrienko, Albert-László Barabási +36

The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when…

stat.OT2020★ 102 cited

A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models

Dianbo Liu, Leonardo Clemente, Canelle Poirier +5

We present a timely and novel methodology that combines disease estimates from mechanistic models with digital traces, via interpretable machine-learning methodologies, to reliably…

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