156 citations
- Amazon (United States)US12 papers
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- National Yang Ming Chiao Tung UniversityTW3 papers
4 papers · 2 filters
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
We discuss promising recent contributions on quantifying feature relevance using Shapley values, where we observed some confusion on which probability distribution is the right one…
Causal Regularization
Dominik Janzing
I argue that regularizing terms in standard regression methods not only help against overfitting finite data, but sometimes also yield better causal models in the infinite sample r…
Deep Gaussian Processes for Multi-fidelity Modeling
Kurt Cutajar, Mark Pullin, Andreas Damianou +2
Multi-fidelity methods are prominently used when cheaply-obtained, but possibly biased and noisy, observations must be effectively combined with limited or expensive true data in o…
Continual Learning in Practice
Tom Diethe, Tom Borchert, Eno Thereska +2
This paper describes a reference architecture for self-maintaining systems that can learn continually, as data arrives. In environments where data evolves, we need architectures th…