- DeepMind Relies on this Old Statistical Method to Build Fair Machine Learning Models - Oct 23, 2020.
Causal Bayesian Networks are used to model the influence of fairness attributes in a dataset.
Bayesian Networks, Bias, DeepMind, Machine Learning
- DeepMind is Using This Old Technique to Evaluate Fairness in Machine Learning Models - Oct 28, 2019.
Visualizing the datasets is an essential component to identify potential sources of bias and unfairness. DeepMind relied on a method called Causal Bayesian networks (CBNs) to represent and estimate unfairness in a dataset.
Bayesian Networks, DeepMind, Machine Learning
- The Book of Why - Jun 1, 2018.
Judea Pearl has made noteworthy contributions to artificial intelligence, Bayesian networks, and causal analysis. These achievements notwithstanding, Pearl holds some views many statisticians may find odd or exaggerated.
Bayesian Networks, Causality, Data Science, Judea Pearl, Simpson's Paradox, Statistics
- THE BOOK OF WHY: The New Science of Cause and Effect - May 15, 2018.
A Turing Prize-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize AI.
AI, Bayesian Networks, Book, Causality, Causation, Judea Pearl
- What is a Bayesian Neural Network? - Dec 5, 2017.
BNNs are important in specific settings, especially when we care about uncertainty very much.
Bayesian, Bayesian Networks, Neural Networks
- How Bayesian Networks Are Superior in Understanding Effects of Variables - Nov 9, 2017.
Bayes Nets have remarkable properties that make them better than many traditional methods in determining variables’ effects. This article explains the principle advantages.
Bayesian, Bayesian Networks, Predictive Models, Probability, Regression, Statistics