Approximating the Manifold Structure of Attributed Incentive Salience from Large Scale Behavioural Data. A Representation Learning Approach Based on Artificial Neural Networks

1 code implementation • 3 Aug 2021 • Valerio Bonometti, Mathieu J. Ruiz, Anders Drachen, Alex Wade

Incentive salience attribution can be understood as a psychobiological mechanism ascribing relevance to potentially rewarding objects and actions.

Representation Learning

From Theory to Behaviour: Towards a General Model of Engagement

1 code implementation • 27 Apr 2020 • Valerio Bonometti, Charles Ringer, Mathieu Ruiz, Alex Wade, Anders Drachen

In the present work we operationalize engagement mechanistically by linking it directly to human behaviour and show that the construct of engagement can be used for shaping and interpreting data-driven methods.

CORD-19: The COVID-19 Open Research Dataset

4 code implementations • ACL 2020 • Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, Russell Reas, Jiangjiang Yang, Doug Burdick, Darrin Eide, Kathryn Funk, Yannis Katsis, Rodney Kinney, Yunyao Li, Ziyang Liu, William Merrill, Paul Mooney, Dewey Murdick, Devvret Rishi, Jerry Sheehan, Zhihong Shen, Brandon Stilson, Alex Wade, Kuansan Wang, Nancy Xin Ru Wang, Chris Wilhelm, Boya Xie, Douglas Raymond, Daniel S. Weld, Oren Etzioni, Sebastian Kohlmeier

The COVID-19 Open Research Dataset (CORD-19) is a growing resource of scientific papers on COVID-19 and related historical coronavirus research.

Information Retrieval Management +1