Her primary areas of study are World Wide Web, Visualization, The Internet, Artificial intelligence and Data visualization. Her Participatory culture study in the realm of World Wide Web interacts with subjects such as Expression, Thriving and Context. Her Artificial intelligence research includes themes of Machine learning and Data mining.
Fernanda B. Viégas has researched Machine learning in several fields, including Inference and Mobile device. Her Data visualization research is multidisciplinary, incorporating elements of Citizen journalism, Tag cloud, Typography and Text mining. Her Deep learning study combines topics in areas such as Information extraction and Distributed computing.
Her primary areas of investigation include Visualization, World Wide Web, Data visualization, Artificial intelligence and Human–computer interaction. The Information visualization research Fernanda B. Viégas does as part of her general Visualization study is frequently linked to other disciplines of science, such as Public space, Metaphor, Government and Software deployment, therefore creating a link between diverse domains of science. Her work on The Internet, Upload and Social data analysis as part of general World Wide Web study is frequently connected to Context and Online encyclopedia, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
As part of one scientific family, she deals mainly with the area of Data visualization, narrowing it down to issues related to the Tag cloud, and often Text mining. Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Natural language processing. Fernanda B. Viégas has included themes like Contextual image classification and Interpretation in her Artificial neural network study.
The concepts of her Deep learning study are interwoven with issues in Algorithm and Image retrieval. Her study looks at the relationship between Image and fields such as Salience, as well as how they intersect with chemical problems. Her studies in Data visualization integrate themes in fields like Data modeling and Interactive visualization.
The scientist’s investigation covers issues in Artificial intelligence, Syntax, Geometry, Linear subspace and Transformer. Her Artificial intelligence study combines topics from a wide range of disciplines, such as Data modeling and Machine learning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martín Abadi;Ashish Agarwal;Paul Barham;Eugene Brevdo.
arXiv: Distributed, Parallel, and Cluster Computing (2015)
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
Melvin Johnson;Mike Schuster;Quoc V. Le;Maxim Krikun.
Transactions of the Association for Computational Linguistics (2017)
Studying cooperation and conflict between authors with history flow visualizations
Fernanda B. Viégas;Martin Wattenberg;Kushal Dave.
human factors in computing systems (2004)
SmoothGrad: removing noise by adding noise
Daniel Smilkov;Nikhil Thorat;Been Kim;Fernanda B. Viégas.
arXiv: Learning (2017)
ManyEyes: a Site for Visualization at Internet Scale
F.B. Viegas;M. Wattenberg;F. van Ham;J. Kriss.
IEEE Transactions on Visualization and Computer Graphics (2007)
How to Use t-SNE Effectively
Martin Wattenberg;Fernanda Viégas;Ian Johnson.
Participatory Visualization with Wordle
F.B. Viegas;M. Wattenberg;J. Feinberg.
IEEE Transactions on Visualization and Computer Graphics (2009)
Talk Before You Type: Coordination in Wikipedia
F.B. Viegas;M. Wattenberg;J. Kriss;F. van Ham.
hawaii international conference on system sciences (2007)
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim;Martin Wattenberg;Justin Gilmer;Carrie Jun Cai.
international conference on machine learning (2018)
The Word Tree, an Interactive Visual Concordance
M. Wattenberg;F.B. Viegas.
IEEE Transactions on Visualization and Computer Graphics (2008)
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