Articles, newest first
Why Longer Survival After Diagnosis Can Mislead
Survival after diagnosis depends on when the clock starts and who enters the denominator. A worked cohort separates those changes from an actual reduction in...
Read article
A Meta-Analysis Is Not a Magic Upgrade
A pooled estimate can be very precise and still be scientifically weak. The quality of a meta-analysis depends on the studies that entered it, the question t...
Read article
Group Averages: What Store-Level Data Cannot Tell You About Customers
The store-level scatter is beautiful: a correlation of 0.77 across a thousand stores, with a confidence interval you could measure with a ruler. The customer...
Read article
Consistency Regularisation Is an Invariance Assumption, Not Free Supervision
Consistency regularisation is often presented as a way to extract supervision from unlabelled data by requiring stable predictions under perturbation. The su...
Read article
The Role of Reinforcement Learning in Optimizing Maintenance Strategies: Dynamic Predictive Maintenance Through Reward-Based Learning
Reinforcement Learning (RL) brings intelligent autonomy to industrial maintenance, enabling dynamic optimization through trial-and-error interaction with com...
Read article
Why SMOTE Isn't Always the Answer
SMOTE generates synthetic samples to rebalance datasets, but using it blindly can create unrealistic data and biased models.
Read articleEntropy Minimisation Can Make the Wrong Answer More Confident
Entropy minimisation encourages decisive predictions on unlabelled data. That can be useful when decision boundaries should avoid high-density regions, but l...
Read article
Why Data Ethics Matters in Machine Learning
Ethical considerations are critical when deploying machine learning systems that affect real people.
Read article
Model Deployment: Best Practices and Tips
Deploying machine learning models to production requires planning and robust infrastructure. Here are key practices to ensure success.
Read article
A Wrong Forward Model Can Produce a Precise Wrong Inverse
Measurement noise and model discrepancy are not the same object. If a forward model is structurally wrong, parameter estimation can absorb the discrepancy an...
Read article