Seldon Research

There is an increasing awareness among practitioners that data drift poses a challenge to the robust deployment of machine learning models. But what precisely is meant by “drift” and how can we protect ourselves against it? 👇📽️ 🧵 youtube.com/watch?v=JaPMFf…

Check out Alex's (@oblibob) blog post on generative modelling using vector-quantized VAEs! seldon.io/generative-mod…

We have a paper accepted into the R2HCAI workshop titled, Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning. 🙌 Very excited to be a part of the conversation around the advances of responsible AI. 💪 Learn more: r2hcai.github.io/AAAI-23/index.… #AAAI

For more details, check out our example benchmarking drift detectors with the KeOps backend here: docs.seldon.io/projects/alibi…

This drastically speeds and scales up the detectors to large dataset sizes, with dataset sizes in the order of 100,000’s easily achievable on a single consumer grade GPU.

We are excited to announce the release of Alibi Detect v0.11.0, featuring widened serialisation support and a new backend that allows drift detection to be rapidly performed on large datasets. seldon.io/alibi-detect-v…

Much more information on Permutation Importance and Partial Dependence Variance, including worked examples, can be found on our documentation pages: docs.seldon.io/projects/alibi… docs.seldon.io/projects/alibi…

Both of these insights are complementary as PI captures not only main feature effects but also interactions, and we recommend considering both, when possible, for a thorough analysis of model behaviour.

We are pleased to announce the release of Alibi Explain v0.9.0 with support for calculating global feature importance via Permutation Importance or Partial Dependence Variance. github.com/SeldonIO/alibi

For a more extensive discussion of the method, its usage and examples please visit our documentation page: docs.seldon.io/projects/alibi….

Our PD implementation in Alibi v0.8.0 has the following advantages over other implementations: - Applies to any black-box model - Full support for 1-way, 2-way and higher order PD for numerical and categorical variables - Flexible plotting functionality for 1-way and 2-way PD

We are delighted to announce the release of Alibi Explain github.com/SeldonIO/alibi v0.8.0 featuring support for Partial Dependence plots, enabling global explainability of any model.