Author: che

After an intense and fruitful discussion on Agentic AI thanks to a great presentation from Paul below, we aim to have a look at the practical implementation of Agentic AI on 19th March.

The data science SIG discussed the paper from Larry Wasserman (CMU) on Decorrelated Variable Importance. The standard Leave-Out COvariates (LOCO) estimator is biased. This publication introduces and evaluates four alternatives including methods for optaining confidence intervals. The recommended alternatives are based on non-parametric estimation for decorrelating the set set of interested variables. It provides one-step estimators and the influence functions, a key concept for this estimation. We looked into the related paper Demystifying statistical learning based on efficient influence functions to gain deeper insights into this – frequently overlooked – concept. Additional information can be found in Larry Wasserman’s book All of non-parametric statistics (page 18).

In the next meeting on 6th March we’ll take a look into the topic of Agentic AI.

The DS SIG went through the FDA Guidance to Industry Draft on Bayesian Methods for Drug and Biological Products. The document lays ground for using Bayesian methods for the analysis of Clinical Trials. This is a huge step forward following Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials. It outlines and references requirements for information borrowing, usage of historical data and pediatric extrapolation. It lays out requirements for the determination and acceptance of priors and details how they need to be evaluated for usage in applications to the FDA.

The DS SIG went through the two most recent DeepSeek technical reports to better understand those advancements in AI. Specifically, the following documents were discussed:

• DeepSeek Technical Report V3,
• DeepSeek Technical Report on Manifold Hyper-Constraints,
• Sinkhorn-Knopp-Algorithm on Non-negative matrices used by mHC, and
• Training Very Deep Networks explaining data highways.

In the next session, we’ll look at the current Guidance to Industry draft on Bayesian methods.

On 8th January 2026, the PSI Data Science SIG returned from the holiday period. The meeting was used to provide user accounts to the SIG members to our web platform for blogging, discussions, collaborative editing and file sharing. Each member created an account and password and investigated the digital platform options.

The next meeting on 22nd January will be used for planning the “AI vs Human” webinar.

After our founding in 2017, it was now time to start our long desired blog:

Welcome to the PSI Data Science Special Interest Group!

We are a small goup, welcoming interested members, to discuss Data Science topics, share experience, and form best practices within our biweekly meetings.

We have outlined our mission in these slides.