Search Results for author: Alexandra Luccioni

Found 11 papers, 2 papers with code

What's in the Box? An Analysis of Undesirable Content in the Common Crawl Corpus

no code implementations ACL 2021 Alexandra Luccioni, Joseph Viviano

Whereas much of the success of the current generation of neural language models has been driven by increasingly large training corpora, relatively little research has been dedicated to analyzing these massive sources of textual data.

Analyzing Sustainability Reports Using Natural Language Processing

no code implementations3 Nov 2020 Alexandra Luccioni, Emily Baylor, Nicolas Duchene

Climate change is a far-reaching, global phenomenon that will impact many aspects of our society, including the global stock market \cite{dietz2016climate}.

Question Answering

Considerations, Good Practices, Risks and Pitfalls in Developing AI Solutions Against COVID-19

no code implementations13 Aug 2020 Alexandra Luccioni, Joseph Bullock, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Miguel Luengo-Oroz

The COVID-19 pandemic has been a major challenge to humanity, with 12. 7 million confirmed cases as of July 13th, 2020 [1].

Mapping the Landscape of Artificial Intelligence Applications against COVID-19

no code implementations25 Mar 2020 Joseph Bullock, Alexandra Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Miguel Luengo-Oroz

COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020.

Using Simulated Data to Generate Images of Climate Change

no code implementations26 Jan 2020 Gautier Cosne, Adrien Juraver, Mélisande Teng, Victor Schmidt, Vahe Vardanyan, Alexandra Luccioni, Yoshua Bengio

In our paper, we explore the potential of using images from a simulated 3D environment to improve a domain adaptation task carried out by the MUNIT architecture, aiming to use the resulting images to raise awareness of the potential future impacts of climate change.

Domain Adaptation

On the Morality of Artificial Intelligence

no code implementations26 Dec 2019 Alexandra Luccioni, Yoshua Bengio

Much of the existing research on the social and ethical impact of Artificial Intelligence has been focused on defining ethical principles and guidelines surrounding Machine Learning (ML) and other Artificial Intelligence (AI) algorithms [IEEE, 2017, Jobin et al., 2019].

Establishing an Evaluation Metric to Quantify Climate Change Image Realism

no code implementations22 Oct 2019 Sharon Zhou, Alexandra Luccioni, Gautier Cosne, Michael S. Bernstein, Yoshua Bengio

Because metrics for comparing the realism of different modes in a conditional generative model do not exist, we propose several automated and human-based methods for evaluation.

Quantifying the Carbon Emissions of Machine Learning

1 code implementation21 Oct 2019 Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, Thomas Dandres

From an environmental standpoint, there are a few crucial aspects of training a neural network that have a major impact on the quantity of carbon that it emits.

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks

no code implementations2 May 2019 Victor Schmidt, Alexandra Luccioni, S. Karthik Mukkavilli, Narmada Balasooriya, Kris Sankaran, Jennifer Chayes, Yoshua Bengio

We present a project that aims to generate images that depict accurate, vivid, and personalized outcomes of climate change using Cycle-Consistent Adversarial Networks (CycleGANs).

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