290 citations · 1.2k across the 29 of their papers we have counts for
5 papers · 1 filter
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence
Kacper Sokol, Peter Flach
Explainable artificial intelligence and interpretable machine learning are research domains growing in importance. Yet, the underlying concepts remain somewhat elusive and lack gen…
Classifier Calibration: A survey on how to assess and improve predicted class probabilities
Telmo Silva Filho, Hao Song, Miquel Perello-Nieto +3
This paper provides both an introduction to and a detailed overview of the principles and practice of classifier calibration. A well-calibrated classifier correctly quantifies the…
Risk Sensitive Model-Based Reinforcement Learning using Uncertainty Guided Planning
Stefan Radic Webster, Peter Flach
Identifying uncertainty and taking mitigating actions is crucial for safe and trustworthy reinforcement learning agents, especially when deployed in high-risk environments. In this…
You Only Write Thrice: Creating Documents, Computational Notebooks and Presentations From a Single Source
Kacper Sokol, Peter Flach
Academic trade requires juggling multiple variants of the same content published in different formats: manuscripts, presentations, posters and computational notebooks. The need to…
Continual Density Ratio Estimation in an Online Setting
Yu Chen, Song Liu, Tom Diethe +1
In online applications with streaming data, awareness of how far the training or test set has shifted away from the original dataset can be crucial to the performance of the model.…