2 citations · 2 across the 5 of their papers we have counts for
5 papers
FADEx: Feature Attribution and Distortion-based Explanation of Dimensionality Reduction
Lucas Greff Meneses, Evandro S. Ortigossa, Claudio Silva +1
Dimensionality Reduction (DR) is a fundamental tool for high-dimensional data exploration, reducing the complexity of latent spaces of machine learning models, and assisting in the…
TiVy: Time Series Visual Summary for Scalable Visualization
Gromit Yeuk-Yin Chan, Luis Gustavo Nonato, Themis Palpanas +2
Visualizing multiple time series presents fundamental tradeoffs between scalability and visual clarity. Time series capture the behavior of many large-scale real-world processes, f…
MOUNTAINEER: Topology-Driven Visual Analytics for Comparing Local Explanations
Parikshit Solunke, Vitoria Guardieiro, Joao Rulff +5
With the increasing use of black-box Machine Learning (ML) techniques in critical applications, there is a growing demand for methods that can provide transparency and accountabili…
Exploring the Relationship Between Feature Attribution Methods and Model Performance
Priscylla Silva, Claudio T. Silva, Luis Gustavo Nonato
Machine learning and deep learning models are pivotal in educational contexts, particularly in predicting student success. Despite their widespread application, a significant gap p…
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients
Evandro S. Ortigossa, Fábio F. Dias, Brian Barr +2
The development of machine learning applications has increased significantly in recent years, motivated by the remarkable ability of learning-powered systems to discover and genera…