To boost interpretability with concept vectors, a reverse engineering approach automates concept identification by analyzing the latent space of deep neural networks using Singular Value Decomposition. This framework combines factorization, latent space c... read more of Unique Concept Vectors through Latent Space Decomposition

Conclusive Local Interpretation Rules for Random Forests through LionForests read more of LionForests v2

A Visualisation Tool for Interpretable Predictive Maintenance read more of VisioRed

Argumentative Explanations through Local Interpretations of Predictive Models read more of Altruist

A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information read more of LioNets v2

Interactive dialogue between user-machine learning model via explanations read more of LionForests Bot

LioNets technique applied to the Turbofan Engine Degradation Simulation dataset (time-series data) LioNets on Time Series read more of LioNets on Time Series

LioNets: Local Interpretations Of Neural Networks through Penultimate Layer Decoding read more of LioNets

Local Interpretation of Random Forests read more of LionForests