43 citations
- Academy of AthensGR1 paper
- Bear ValleyUS1 paper
- Chinese Academy of SciencesCN1 paper
- Consejo Nacional de Investigaciones Científicas y TécnicasAR1 paper
- Drexel UniversityUS1 paper
- Fundación Ciencias Exactas y NaturalesAR1 paper
- Goddard Space Flight CenterUS1 paper
- Google DeepMind (United Kingdom)GB1 paper
- Google (United States)US1 paper
- Imperial College LondonGB1 paper
- Institute of Engineering ThermophysicsCN1 paper
- Institute of Materials Research and EngineeringSG1 paper
4 papers
Advancing Community Engaged Approaches to Identifying Structural Drivers of Racial Bias in Health Diagnostic Algorithms
Jill A. Kuhlberg, Irene Headen, Ellis A. Ballard +1
Much attention and concern has been raised recently about bias and the use of machine learning algorithms in healthcare, especially as it relates to perpetuating racial discriminat…
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics
Donald Martin, Vinodkumar Prabhakaran, Jill Kuhlberg +2
Recent research on algorithmic fairness has highlighted that the problem formulation phase of ML system development can be a key source of bias that has significant downstream impa…
Machine Learning for Novel Thermal-Materials Discovery: Early Successes, Opportunities, and Challenges
Hang Zhang, Kedar Hippalgaonkar, Tonio Buonassisi +3
High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research…
25 Years of Self-Organized Criticality: Numerical Detection Methods
R. T. James McAteer, Markus J. Aschwanden, Michaila Dimitropoulou +5
The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explos…